People_

Professor Junbin Gao

BSc HUST; MSc HUST; PhD DUT

Professor

Phone

+61 2 8627 4856

junbin.gao@sydney.edu.au

Details

Member of Sydney Southeast Asia Centre

Biographical details

Junbin Gao is Professor of Big Data Analytics at the University of Sydney Business School. Prior to joining the University of Sydney in 2016, he was Professor in Computing from 2010 to 2016 and Associate Professor from 2005 to 2010 at Charles Sturt University (CSU). He was Senior Lecturer from Jan 2005 to July 2005 and Lecturer from Nov 2001 to Jan 2005 in the School of Mathematics, Statistics and Computer Science (now the School of Science and Technology) at University of New England (UNE). Between 1999 and 2001, he worked as a Research Fellow in the Department of Electronics and Computer Science at University of Southampton, England.

Research interests

Professor Junbin Gao began his research career by studying approximation theory and application of multivariate spline functions in numerical solutions for partial differential equations, continuing research work in wavelet applications in chemometrics, and becoming an outstanding researcher in machine learning, pattern recognition, Bayesian learning/inference, numerical optimisation and big data analytics in business.

One of interesting examples in Junbin’s recent research is to propose matrix neural networks and apply it in longitudinal relational data in politics research, where he further develops it to tensorial recurrent neural network. In a series of papers from 2014 to 2017 Junbin Gao showed how to conduct data subspace clustering and dimensionality reduction on manifolds particularly for the abstract Grassmann manifolds. Much of this work has been joint with a number of international collaborators. Junbin Gao’s work prior to 2014 is on dimensionality reduction, which was funded by the Australian Research Council (ARC), and the success can be seen in a series of paper between 2005 and 2013 and the research was quoted by The Australian newspaper in 2012.

More recently Junbin has focussed on designing machine learning algorithms for structural data such as tensor-valued data and manifold-valued data widely seen modern business and computer vision. In classical data analysis and machine learning algorithms, input data including manifold-valued data are generally regarded as or converted to vectorial data in a Euclidean space by ignoring useful prior information. However, for manifold-valued data, it is unclear how to extend those very powerful machine learning algorithms for vectorial data, such as the state-of-the-art Low Rank Representation models, onto general Riemannian manifolds due to loss of linearity structures over “curved” Riemannian manifolds.

In recent years there has been great progress in the research of commonly used matrix manifolds such as the tensor manifold/covariance descriptor, Stiefel manifold, Multinomial Manifold, Grassmann manifold, Kendall Shape manifolds and Low Rank matrix manifold. The core idea is to explicitly incorporate geometry of manifolds for the purpose of learning algorithm design, which brings advantages of improving accuracy and efficiency and reducing computational cost of conventional machine learning algorithms. So answering questions about manifold-valued data modelling forces us to consider how sufficiently using Riemannian properties of the well-known matrix manifolds to assist designing new learning algorithms for manifold-valued data analysis.

There are applications in many areas, but Junbin Gao has a particular interest in what happens in international relation research and panel data in financial world, and also learning tasks in pattern analysis for computer vision tasks.

Teaching and supervision

BUSS4001 Business Honours Research Methods
BUSS4313 Business Analytics Honours B
QBUS5001 Quantitative Methods for Business
QBUS6810 Statistical Learning and Data Mining
QBUS6840 Predictive Analytics

Current research students

Project title	Research student
Multivariate Volatility Forecast via Spatiotemporal Methods	Mike CHI
Interpretable uncertainty system identification: A multi-dimensional time series forecasting technology of financial data.	Jiayu FANG
Banking Corporate Innovation and Deep Learning	Yunying HUANG
Machine Learning-Based Systematic Analysis of Social Media Polarization: Detection, Root Cause Analysis, and Mitigation Strategies	Levia LI
Graph Neural Networks	Lena LIN
Deep learning in Financial Time Series Forecasting	Chen LIU
Research on the Explainability of Machine Learning and Artificial Intelligence in Business Analytics	Hongwei MA
Beyond Trade-Offs: Advancing Spatial-Temporal Forecasting in Transportation with Deep Learning	Jessica SHAO
DEEP LEARNING OPTIMIZATION TO PREDICT STOCK MARKET MOVEMENT USING FUNDAMENTAL AND TECHNICAL ANALYSIS	Widhiyo SUDIYONO
Enhancing representation learning in Graph Neural Network	Ye XIAO
Trustworthy Machine Learning	Kuan YAN
ESG and Portfolio Performance Optimization with Advanced Machine Learning Techniques：evidence from China	Xuan YE
Actuarial Studies with machine learning and statistical modelling	Yuning ZHANG

Selected publications

Multimodal Analytics for Next-Generation Big Data Technologies and Applications

(Springer International Publishing, 2019)

Publications

By Type

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Edited Books

Seng, K., Ang, L., Liew, A., Gao, J. (2019). Multimodal Analytics for Next-Generation Big Data Technologies and Applications. Cham: Springer International Publishing. [More Information]
Gao, J., Kwan, P., Poon, J., Poon, S. (2009). Proceedings of the Workshop Advances and Issues in Biomedical Data Mining (AIBDM'09). Thailand: Printing House of Thammasat University - Rangsit Campus.

Book Chapters

Yates, D., Islam, Z., Gao, J. (2019). Implementation and Performance Analysis of Data-Mining Classification Algorithms on Smartphones. In R. Islam, Y. S. Koh, Y. Zhao, G. Warwick, D. Stirling, C-T. Li, Z. Islam (Eds.), Data Mining: 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised selected papers, (pp. 331-343). Singapore: Springer. [More Information]
Soomro, T., Gao, J., Zheng, L., Afifi, A., Soomro, S., Paul, M. (2019). Retinal Blood Vessels Extraction of Challenging Images. In R. Islam, Y. S. Koh, Y. Zhao, G. Warwick, D. Stirling, C-T. Li, Z. Islam (Eds.), Data Mining: 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised selected papers, (pp. 347-359). Singapore: Springer. [More Information]
Yates, D., Islam, M., Gao, J. (2019). SPAARC: A Fast Decision Tree Algorithm. In R. Islam, Y. S. Koh, Y. Zhao, G. Warwick, D. Stirling, C-T. Li, Z. Islam (Eds.), Data Mining: 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised selected papers, (pp. 43-55). Singapore: Springer. [More Information]
Wang, B., Gao, J. (2019). Unsupervised Learning on Grassmann Manifolds for Big Data. In K. Seng, L. Ang, A. Liew, J. Gao (Eds.), Multimodal Analytics for Next-Generation Big Data Technologies and Applications, (pp. 151-180). Cham: Springer International Publishing. [More Information]
Jiang, X., Gao, J., Liu, X., Cai, Z., Zhang, D., Liu, Y. (2018). Shared Deep Kernel Learning for Dimensionality Reduction. In Phung D., Tseng V., Webb G., Ho B., Ganji M., Rashidi L. (Eds.), Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, PAKDD 2018 Melbourne, VIC, Australia, June 3–6, 2018 Proceedings, Part III, (pp. 297-308). Cham: Springer. [More Information]
Wang, P., He, Z., Xie, K., Gao, J., Antolovich, M. (2017). A Nonnegative Projection Based Algorithm for Low-Rank Nonnegative Matrix Approximation. In Derong Liu, Shengli Xie, Yuanqing Li, Dongbin Zhao, El-Sayed M. El-Alfy (Eds.), Neural Information Processing: 24th International Conference, ICONIP 2017 Guangzhou, China, November 14-18, 2017 Proceedings, Part I, (pp. 240-247). Cham: Springer. [More Information]
Zhang, Y., Gao, J. (2017). Assessing the Performance of Deep Learning Algorithms for Newsvendor Problem. In Derong Liu, Shengli Xie, Yuanqing Li, Dongbin Zhao, El-Sayed M. El-Alfy (Eds.), Neural Information Processing: 24th International Conference, ICONIP 2017 Guangzhou, China, November 14-18, 2017 Proceedings, Part I, (pp. 912-921). Cham: Springer. [More Information]
Gao, J., Guo, Y., Wang, Z. (2017). Matrix Neural Networks. In F Cong, A Leung, Q Wei (Eds.), Advances in Neural Networks - ISNN 2017: 14th International Symposium, ISNN 2017, Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21-26, 2017, Proceedings, Part I, (pp. 313-320). Cham: Springer. [More Information]
Bai, M., Zhang, B., Gao, J. (2017). Tensorial Neural Networks and Its Application in Longitudinal Network Data Analysis. In Derong Liu, Shengli Xie, Yuanqing Li, Dongbin Zhao, El-Sayed M. El-Alfy (Eds.), Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part II, (pp. 562-571). Cham: Springer. [More Information]
Abraham, J., Kwan, P., Gao, J. (2011). Fingerprint Matching using A Hybrid Shape and Orientation Descriptor. In Jucheng Yang and Loris Nanni (Eds.), State of the art in Biometrics, (pp. 25-56). Rijeka, Croatia: InTech Publishers. [More Information]

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Journals

Wang, B., Ma, Y., Li, X., Gao, J., Hu, Y., Yin, B. (2025). Bridging the Cross-Modality Semantic Gap in Visual Question Answering. IEEE Transactions on Neural Networks and Learning Systems, 36(3), 4519-4531. [More Information]
Shi, D., Han, A., Lin, L., Guo, Y., Wang, Z., Gao, J. (2025). Design your own universe: a physics-informed agnostic method for enhancing graph neural networks. International Journal of Machine Learning and Cybernetics, 16(2), 1129-1144. [More Information]
Wang, J., Guo, J., Sun, Y., Gao, J., Wang, S., Yang, Y., Yin, B. (2025). DGNN: Decoupled Graph Neural Networks With Structural Consistency Between Attribute and Graph Embedding Representations. IEEE Transactions on Big Data, Published online: 31 October 2024. [More Information]
Shi, D., Shao, Z., Gao, J., Wang, Z., Guo, Y. (2025). Frameless Graph Knowledge Distillation. IEEE Transactions on Neural Networks and Learning Systems, Published online: 4 September 2024. [More Information]
Liu, H., Wang, B., Sun, Y., Gao, J., Li, X., Hu, Y., Yin, B. (2025). Multi-granularity Feature Interaction and Multi-region Selection based Triplet Visual Question Answering. IEEE Transactions on Big Data, Published online: 3 September 2024. [More Information]
Yang, M., Shi, D., Zheng, X., Yin, J., Gao, J. (2025). Quasi-framelets: robust graph neural networks via adaptive framelet convolution. International Journal of Machine Learning and Cybernetics, 16(2), 755-770. [More Information]
Shao, Z., Yao, X., Chen, F., Wang, Z., Gao, J. (2025). Revisiting time-varying dynamics in stock market forecasting: A multi-source sentiment analysis approach with large language model. Decision Support Systems, 190, 114362. [More Information]
Shao, Z., Wang, Z., Yao, X., Bell, M., Gao, J. (2025). ST-MambaSync: Complement the power of Mamba and Transformer fusion for less computational cost in spatial–temporal traffic forecasting. Information Fusion, 117, 102872. [More Information]
Liu, T., Hu, Y., Li, M., Yi, J., Chang, X., Gao, J., Yin, B. (2025). Tackling Real-world Complexity: Hierarchical Modeling and Dynamic Prompting for Multimodal Long Document Classification. IEEE Transactions on Circuits and Systems for Video Technology, Published online: 3 February 2025. [More Information]
Zhang, Q., Sun, Y., Wang, S., Gao, J., Hu, Y., Yin, B. (2025). Training Large-Scale Graph Neural Networks Via Graph Partial Pooling. IEEE Transactions on Big Data, 11(1), 221-233. [More Information]
Cheng, C., Zhang, L., Li, H., Cui, W., Gao, J., Cun, Y. (2024). A Deep High-Order Tensor Sparse Representation for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 62, 5521416. [More Information]
Yang, Y., Sun, Y., Wang, S., Gao, J., Ju, F., Yin, B. (2024). A Dual-Masked Deep Structural Clustering Network With Adaptive Bidirectional Information Delivery. IEEE Transactions on Neural Networks and Learning Systems, 35(10), 14783-14796. [More Information]
Uddin, S., Lu, H., Rahman, A., Gao, J. (2024). A novel approach for assessing fairness in deployed machine learning algorithms. Scientific Reports, 14(1), 17753. [More Information]
Zou, C., Han, A., Lin, L., Li, M., Gao, J. (2024). A Simple Yet Effective Framelet-Based Graph Neural Network for Directed Graphs. IEEE Transactions on Artificial Intelligence, 5(4), 1647-1657. [More Information]
Zhang, Q., Li, J., Sun, Y., Wang, S., Gao, J., Yin, B. (2024). Beyond low-pass filtering on large-scale graphs via Adaptive Filtering Graph Neural Networks. Neural Networks, 169, 1-10. [More Information]
Guo, K., Yin, B., Tian, D., Hu, Y., Lin, C., Qian, Z., Sun, Y., Zhou, J., Duan, X., Gao, J. (2024). CFMMC-Align: Coarse-Fine Multi-Modal Contrastive Alignment Network for Traffic Event Video Question Answering. IEEE Transactions on Circuits and Systems for Video Technology, 34(11), 10538-10550. [More Information]
Guo, K., Tian, D., Hu, Y., Sun, Y., Qian, S., Zhou, J., Gao, J., Yin, B. (2024). Contrastive learning for traffic flow forecasting based on multi graph convolution network. IET Intelligent Transport Systems, 18(2), 290-301. [More Information]
Guo, K., Tian, D., Zhou, J., Hu, Y., Sun, Y., Yin, B., Gao, J., Qian, S. (2024). Contrastive optimized graph convolution network for traffic forecasting. Neurocomputing, 602, 128249. [More Information]
Liu, T., Hu, Y., Gao, J., Sun, Y., Yin, B. (2024). Cross-modal Multiple Granularity Interactive Fusion Network for Long Document Classification. ACM Transactions on Knowledge Discovery from Data, 18(4), 78. [More Information]
Han, A., Mishra, B., Jawanpuria, P., Gao, J. (2024). Differentially private Riemannian optimization. Machine Learning, 113(3), 1133-1161. [More Information]
Lin, L., Li, Z., Li, R., Li, X., Gao, J. (2024). Diffusion models for time-series applications: a survey. Frontiers of Informaion Technology & Electronic Engineering, 25(1), 19-41. [More Information]
Shao, J., Shi, D., Han, A., Vasnev, A., Guo, Y., Gao, J. (2024). Enhancing framelet GCNs with generalized p-Laplacian regularization. International Journal of Machine Learning and Cybernetics, 15(4), 1553-1573. [More Information]
Chen, J., Chen, S., Gao, J., Huang, Z., Zhang, J., Pu, J. (2024). Exploiting Neighbor Effect: Conv-Agnostic GNN Framework for Graphs With Heterophily. IEEE Transactions on Neural Networks and Learning Systems, 35(10), 13383-13396. [More Information]
Zhou, B., Li, R., Zheng, X., Wang, Y., Gao, J. (2024). Graph Denoising with Framelet Regularizers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12), 7606-7617. [More Information]
Liu, T., Hu, Y., Gao, J., Sun, Y., Yin, B. (2024). Hierarchical Multi-granularity Interaction Graph Convolutional Network for Long Document Classification. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 32, 1762-1775. [More Information]
Liu, T., Hu, Y., Gao, J., Sun, Y., Yin, B. (2024). Hierarchical Multi-modal Prompting Transformer for Multi-modal Long Document Classification. IEEE Transactions on Circuits and Systems for Video Technology, 34(7), 6376-6390. [More Information]
Zhang, H., Gao, J., Qian, J., Yang, J., Xu, C., Zhang, B. (2024). Linear Regression Problem Relaxations Solved by Nonconvex ADMM with Convergence Analysis. IEEE Transactions on Circuits and Systems for Video Technology, 34(2), 828-838. [More Information]
Wang, J., Wang, B., Gao, J., Pan, S., Liu, T., Yin, B., Gao, W. (2024). MADE: Multicurvature Adaptive Embedding for Temporal Knowledge Graph Completion. IEEE Transactions on Cybernetics, 54(10), 5818-5831. [More Information]
He, X., Wang, B., Gao, J., Wang, Q., Hu, Y., Yin, B. (2024). Mixed-modality Clustering via Generative Graph Structure Matching. IEEE Transactions On Knowledge And Data Engineering, 36(12), 8773-8786. [More Information]
Wang, B., Wu, G., Li, X., Gao, J., Hu, Y., Yin, B. (2024). Modality Perception Learning-Based Determinative Factor Discovery for Multimodal Fake News Detection. IEEE Transactions on Neural Networks and Learning Systems, Published online: 20 September 2024. [More Information]
Wang, J., Wang, B., Gao, J., Hu, S., Hu, Y., Yin, B. (2024). Multi-Level Interaction Based Knowledge Graph Completion. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 32, 386-396. [More Information]
Liu, T., Hu, Y., Gao, J., Wang, J., Sun, Y., Yin, B. (2024). Multi-modal long document classification based on Hierarchical Prompt and Multi-modal Transformer. Neural Networks, 176, 106322. [More Information]
He, X., Wang, B., Luo, C., Gao, J., Hu, Y., Yin, B. (2024). Multi-view subspace clustering with incomplete graph information. IET Computer Vision, Published online: 17 July 2022. [More Information]
He, X., Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2024). Parallelly Adaptive Graph Convolutional Clustering Model. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 4451-4464. [More Information]
Wang, J., Wang, B., Gao, J., Li, X., Hu, Y., Yin, B. (2024). QDN: A Quadruplet Distributor Network for Temporal Knowledge Graph Completion. IEEE Transactions on Neural Networks and Learning Systems, 35(10), 14018-14030. [More Information]
Shi, D., Shao, Z., Guo, Y., Zhao, Q., Gao, J. (2024). Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and as Non-Linear Diffusion. Transactions on Machine Learning Research, 2, 1-27.
Han, A., Mishra, B., Jawanpuria, P., Gao, J. (2024). Riemannian block SPD coupling manifold and its application to optimal transport. Machine Learning, 113(4), 1595-1622. [More Information]
Wen, H., Chen, T., Chai, L., Sadiq, S., Gao, J., Yin, H. (2024). Variational Counterfactual Prediction under Runtime Domain Corruption. IEEE Transactions On Knowledge And Data Engineering, 36(5), 2271-2284. [More Information]
Huo, G., Zhang, Y., Gao, J., Wang, B., Hu, Y., Yin, B. (2023). CaEGCN: Cross-Attention Fusion Based Enhanced Graph Convolutional Network for Clustering. IEEE Transactions On Knowledge And Data Engineering, 35(4), 3471-3483. [More Information]
Li, Y., Bai, M., Guan, Q., Ming, Z., Liang, X., Liu, G., Gao, J. (2023). CSD-RkNN: reverse k nearest neighbors queries with conic section discriminances. International Journal of Geographical Information Science, 37(10), 2175-2204. [More Information]
Long, T., Sun, Y., Gao, J., Hu, Y., Yin, B. (2023). Domain Adaptation as Optimal Transport on Grassmann Manifolds. IEEE Transactions on Neural Networks and Learning Systems, 34(10), 7196-7209. [More Information]
Liang, H., Du, X., Zhu, B., Ma, Z., Chen, K., Gao, J. (2023). Graph contrastive learning with implicit augmentations. Neural Networks, 163, 156-164. [More Information]
Chen, J., Chen, S., Bai, M., Pu, J., Zhang, J., Gao, J. (2023). Graph Decoupling Attention Markov Networks for Semisupervised Graph Node Classification. IEEE Transactions on Neural Networks and Learning Systems, 34(12), 9859-9873. [More Information]
He, X., Wang, B., Li, R., Gao, J., Hu, Y., Huo, G., Yin, B. (2023). Graph structure learning layer and its graph convolution clustering application. Neural Networks, 165, 1010-1020. [More Information]
Hu, Y., Peng, T., Guo, K., Sun, Y., Gao, J., Yin, B. (2023). Graph transformer based dynamic multiple graph convolution networks for traffic flow forecasting. IET Intelligent Transport Systems, 17(9), 1835-1845. [More Information]
Liu, T., Hu, Y., Wang, B., Sun, Y., Gao, J., Yin, B. (2023). Hierarchical Graph Convolutional Networks for Structured Long Document Classification. IEEE Transactions on Neural Networks and Learning Systems, 34(10), 8071-8085. [More Information]
Huo, G., Zhang, Y., Wang, B., Gao, J., Hu, Y., Yin, B. (2023). Hierarchical Spatio-Temporal Graph Convolutional Networks and Transformer Network for Traffic Flow Forecasting. IEEE Transactions on Intelligent Transportation Systems, 24(4), 3855-3867. [More Information]
Soomro, T., Zheng, L., Afifi, A., Ali, A., Soomro, S., Yin, M., Gao, J. (2023). Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review. IEEE Reviews in Biomedical Engineering, 16, 70-90. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2023). Logarithmic Schatten-p Norm Minimization for Tensorial Multi-View Subspace Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(3), 3396-3410. [More Information]
Zheng, X., Zhou, B., Li, M., Wang, Y., Gao, J. (2023). MATHNET: Haar-like wavelet multiresolution analysis for graph representation learning. Knowledge-Based Systems, 273, 110609. [More Information]
Wang, J., Wang, B., Gao, J., Hu, Y., Yin, B. (2023). Multi-Concept Representation Learning for Knowledge Graph Completion. ACM Transactions on Knowledge Discovery from Data, 17(1), 11-1-11-19. [More Information]
Yang, Y., Sun, Y., Ju, F., Wang, S., Gao, J., Yin, B. (2023). Multi-graph Fusion Graph Convolutional Networks with pseudo-label supervision. Neural Networks, 158, 305-317. [More Information]
Han, A., Mishra, B., Jawanpuria, P., Gao, J. (2023). Nonconvex-nonconcave min-max optimization on Riemannian manifolds. Transactions on Machine Learning Research, , 1-33. [More Information]
Han, A., Mishra, B., Jawanpuria, P., Kumar, P., Gao, J. (2023). Riemannian Hamiltonian Methods for Min-Max Optimization on Manifolds. SIAM Journal on Optimization, 33(3), 1797-1827. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2023). Robust discriminant analysis with feature selective projection and between-classes structural incoherence. Digital Signal Processing, 134, 103896. [More Information]
Wang, J., Wang, B., Gao, J., Li, X., Hu, Y., Yin, B. (2023). TDN: Triplet Distributor Network for Knowledge Graph Completion. IEEE Transactions On Knowledge And Data Engineering, 35(12), 13002-13014. [More Information]
Hong, X., Gao, J., Wei, H., Xiao, J., Mitchell, R. (2023). Two-step scalable spectral clustering algorithm using landmarks and probability density estimation. Neurocomputing, 519, 173-186. [More Information]
Liang, H., Gao, J. (2023). Wasserstein Adversarially Regularized Graph Autoencoder. Neurocomputing, 541, 126235. [More Information]
Ji, Q., Sun, Y., Gao, J., Hu, Y., Yin, B. (2022). A Decoder-Free Variational Deep Embedding for Unsupervised Clustering. IEEE Transactions on Neural Networks and Learning Systems, 33(10), 5681-5693. [More Information]
Wu, W., Li, B., Chen, L., Gao, J., Zhang, C. (2022). A Review for Weighted MinHash Algorithms. IEEE Transactions On Knowledge And Data Engineering, 34(6), 2553-2573. [More Information]
Guo, Z., Min, A., Yang, B., Chen, J., Li, H., Gao, J. (2022). A Sparse Oblique-Manifold Nonnegative Matrix Factorization for Hyperspectral Unmixing. IEEE Transactions on Geoscience and Remote Sensing, 60, 5508013. [More Information]
Saha, S., Gao, J., Gerlach, R. (2022). A survey of the application of graph-based approaches in stock market analysis and prediction. International Journal of Data Science and Analytics, 14(1), 1-15. [More Information]
Zhao, J., Guo, J., Sun, Y., Gao, J., Wang, S., Yin, B. (2022). Adaptive graph convolutional clustering network with optimal probabilistic graph. Neural Networks, 156, 271-284. [More Information]
Jie, R., Gao, J., Vasnev, A., Tran, M. (2022). Adaptive hierarchical hyper-gradient descent. International Journal of Machine Learning and Cybernetics, 13(12), 3785-3805. [More Information]
Yang, Y., Ju, F., Sun, Y., Gao, J., Yin, B. (2022). Adversarially regularized joint structured clustering network. Information Sciences, 615, 136-151. [More Information]
Xu, J., Zhang, B., Wang, Z., Wang, Y., Chen, F., Gao, J., Feng, D. (2022). Affective Audio Annotation of Public Speeches with Convolutional Clustering Neural Network. IEEE Transactions on Affective Computing, 13(1), 238-249. [More Information]
Guo, K., Hu, Y., Qian, Z., Sun, Y., Gao, J., Yin, B. (2022). An Optimized Temporal-Spatial Gated Graph Convolution Network for Traffic Forecasting. IEEE Intelligent Transportation Systems Magazine, 14(1), 153-162. [More Information]
Soomro, T., Zheng, L., Afifi, A., Ali, A., Yin, M., Gao, J. (2022). Artificial intelligence (AI) for medical imaging to combat coronavirus disease (COVID-19): a detailed review with direction for future research. Artificial Intelligence Review, 55(2), 1409-1439. [More Information]
Cui, Z., Hu, Y., Sun, Y., Gao, J., Yin, B. (2022). Cross-modal alignment with graph reasoning for image-text retrieval. Multimedia Tools and Applications, 81(17), 23615-23632. [More Information]
Sun, Y., Jiang, X., Hu, Y., Duan, F., Guo, K., Wang, B., Gao, J., Yin, B. (2022). Dual Dynamic Spatial-Temporal Graph Convolution Network for Traffic Prediction. IEEE Transactions on Intelligent Transportation Systems, 23(12), 23680-23693. [More Information]
Guo, K., Hu, Y., Qian, Z., Sun, Y., Gao, J., Yin, B. (2022). Dynamic Graph Convolution Network for Traffic Forecasting Based on Latent Network of Laplace Matrix Estimation. IEEE Transactions on Intelligent Transportation Systems, 23(2), 1009-1018. [More Information]
Zhou, B., Zheng, X., Wang, Y., Li, M., Gao, J. (2022). Embedding graphs on Grassmann manifold. Neural Networks, 152, 322-331. [More Information]
Han, A., Gao, J. (2022). Improved Variance Reduction Methods for Riemannian Non-Convex Optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(11), 7610-7623. [More Information]
Yang, J., Ma, J., Win, K., Gao, J., Yang, Z. (2022). Low-rank and sparse representation based learning for cancer survivability prediction. Information Sciences, 582, 573-592. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2022). Multi-Attribute Subspace Clustering via Auto-Weighted Tensor Nuclear Norm Minimization. IEEE Transactions on Image Processing, 31, 7191-7205. [More Information]
Zhu, F., Gao, J., Yang, J., Ye, N. (2022). Neighborhood linear discriminant analysis. Pattern Recognition, 123, 108422. [More Information]
Hu, X., Sun, Y., Gao, J., Hu, Y., Ju, F., Yin, B. (2022). Probabilistic Linear Discriminant Analysis Based on L1-Norm and Its Bayesian Variational Inference. IEEE Transactions on Cybernetics, 52(3), 1616-1627. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2022). Rank Consistency Induced Multiview Subspace Clustering via Low-Rank Matrix Factorization. IEEE Transactions on Neural Networks and Learning Systems, 33(7), 3157-3170. [More Information]
Hu, Y., Luo, C., Gao, J., Wang, B., Sun, Y., Yin, B. (2022). Shareability-Exclusivity Representation on Product Grassmann Manifolds for Multi-camera video clustering. Journal of Visual Communication and Image Representation, 84, 103457. [More Information]
Long, T., Sun, Y., Gao, J., Hu, Y., Yin, B. (2022). Video Domain Adaptation based on Optimal Transport in Grassmann Manifolds. Information Sciences, 594, 151-162. [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Ju, F., Yin, B. (2021). Adaptive Fusion of Heterogeneous Manifolds for Subspace Clustering. IEEE Transactions on Neural Networks and Learning Systems, 32(8), 3484-3497. [More Information]
Hu, Y., Song, Z., Wang, B., Gao, J., Sun, Y., Yin, B. (2021). AKM3C: Adaptive K-Multiple-Means for Multi-view Clustering. IEEE Transactions on Circuits and Systems for Video Technology, 31(11), 4214-4226. [More Information]
Hu, Y., Luo, C., Wang, B., Gao, J., Sun, Y., Yin, B. (2021). Complete/incomplete multi-view subspace clustering via soft block-diagonal-induced regulariser. IEE Proceedings-Vision Image and Signal Processing, 15(8), 618-632. [More Information]
Alam, N., Gao, J., Jones, S. (2021). Corporate Failure Prediction: An Evaluation of Deep Learning vs Discrete Hazard Models. Journal of International Financial Markets, Institutions and Money, 75. [More Information]
Shi, D., Gao, J., Hong, X., Choy, S., Wang, Z. (2021). Coupling matrix manifolds assisted optimization for optimal transport problems. Machine Learning, 110(3), 533-558. [More Information]
Wu, L., Wang, Y., Gao, J., Wang, M., Zha, Z., Tao, D. (2021). Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification. IEEE Transactions on Neural Networks and Learning Systems, 32(2), 722-735. [More Information]
Jie, R., Gao, J. (2021). Differentiable Neural Architecture Search for High-Dimensional Time Series Forecasting. IEEE Access, 9, 20922-20932. [More Information]
Guo, Y., Tierney, S., Gao, J. (2021). Efficient sparse subspace clustering by nearest neighbour filtering. Signal Processing, 185, 108082. [More Information]
Hong, X., Gao, J. (2021). Estimating the square root of probability density function on Riemannian manifold. Expert Systems, 38(7), e12266. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2021). Kronecker-decomposable robust probabilistic tensor discriminant analysis. Information Sciences, 561, 196-210. [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Ju, F., Yin, B. (2021). Learning Adaptive Neighborhood Graph on Grassmann Manifolds for Video/Image-Set Subspace Clustering. IEEE Transactions on Multimedia, 23, 216-227. [More Information]
Tian, S., Liu, X., Liu, M., Bian, Y., Gao, J., Yin, B. (2021). Learning the incremental warp for 3d vehicle tracking in lidar point clouds. Remote Sensing, 13(14), 2770. [More Information]
Xu, D., Bai, M., Long, T., Gao, J. (2021). LSTM-assisted evolutionary self-expressive subspace clustering. International Journal of Machine Learning and Cybernetics, 12(10), 2777-2793. [More Information]
Zhou, B., Gao, J., Tran, M., Gerlach, R. (2021). Manifold optimization Assisted Gaussian Variational Approximation. Journal of Computational and Graphical Statistics, 30(4), 946-957. [More Information]
Wang, M., Jiang, X., Gao, J., Wang, T., Hu, C., Liu, F., Feng, Q. (2021). Minimum unbiased risk estimate based 2DPCA for color image denoising. Neurocomputing, 440, 127-144. [More Information]
Guo, K., Hu, Y., Qian, Z., Liu, H., Zhang, K., Sun, Y., Gao, J., Yin, B. (2021). Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction. IEEE Transactions on Intelligent Transportation Systems, 22(2), 1138-1149. [More Information]
Guo, Y., Tierney, S., Gao, J. (2021). Robust Functional Manifold Clustering. IEEE Transactions on Neural Networks and Learning Systems, 32(2), 777-787. [More Information]
Yin, S., Sun, Y., Gao, J., Hu, Y., Wang, B., Yin, B. (2021). Robust Image Representation via Low Rank Locality Preserving Projection. ACM Transactions on Knowledge Discovery from Data, 15(4), 1-22. [More Information]
Zhang, B., Wang, Z., Gao, J., Rutjes, C., Nufer, K., Tao, D., Feng, D., Menzies, S. (2021). Short-term Lesion Change Detection for Melanoma Screening with Novel Siamese Neural Network. IEEE Transactions on Medical Imaging, 40(3), 840-851. [More Information]
Saha, S., Gao, J., Gerlach, R. (2021). Stock Ranking Prediction Using List-Wise Approach and Node Embedding Technique. IEEE Access, 9, 88981-88996. [More Information]
Chowdhury, M., Gao, J., Islam, R. (2020). Extracting depth information from stereo images using a fast correlation matching algorithm. International Journal of Computers and Applications, 42(8), 798-803. [More Information]
Hu, C., Gao, J., Chen, J., Jiang, D., Shu, Y. (2020). Fine-grained age estimation with multi-attention network. IEEE Access, 8, 196013-196023. [More Information]
Jie, R., Gao, J., Vasnev, A., Tran, M. (2020). HyperTube: A Framework for Population-Based Online Hyperparameter Optimization with Resource Constraints. IEEE Access, 8, 69038-69057. [More Information]
Long, T., Sun, Y., Gao, J., Hu, Y., Yin, B. (2020). Locality preserving projection based on Euler representation. Journal of Visual Communication and Image Representation, 70, 102796. [More Information]
Li, J., Yan, H., Gao, J., Kong, D., Wang, L., Wang, S., Yin, B. (2020). Matrix-variate variational auto-encoder with applications to image process. Journal of Visual Communication and Image Representation, 67, 102750. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2020). Robust Adaptive Linear Discriminant Analysis with Bidirectional Reconstruction Constraint. ACM Transactions on Knowledge Discovery from Data, 14(6), 3409478. [More Information]
Ye, Y., Gao, J., Shao, Y., Li, C., Jin, Y., Hua, X. (2020). Robust support vector regression with generic quadratic nonconvex epsilon-insensitive loss. Applied Mathematical Modelling, 82, 235-251. [More Information]
Hong, X., Gao, J., Chen, S. (2020). Semi-blind joint channel estimation and data detection on sphere manifold for MIMO with high-order QAM signaling. Journal of the Franklin Institute, 357(9), 5680-5697. [More Information]
Wang, P., He, Z., Xie, K., Gao, J., Antolovich, M., Tan, B. (2019). A hybrid algorithm for low-rank approximation of nonnegative matrix factorization. Neurocomputing, 364, 129-137. [More Information]
Khan, M., Khan, T., Soomro, T., Mir, N., Gao, J. (2019). Boosting sensitivity of a retinal vessel segmentation algorithm. Pattern Analysis and Applications, 22(2), 583-599. [More Information]
Zhu, M., Shi, D., Gao, J. (2019). Branched convolutional neural networks incorporated with Jacobian deep regression for facial landmark detection. Neural Networks, 118, 127-139. [More Information]
Xu, C., Yang, J., Gao, J. (2019). Coupled-learning convolutional neural networks for object recognition. Multimedia Tools and Applications, 78(1), 573-589. [More Information]
Wu, L., Wang, Y., Li, X., Gao, J. (2019). Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition. IEEE Transactions on Cybernetics, 49(5), 1791-1802. [More Information]
Soomro, T., Afifi, A., Zheng, L., Soomro, S., Gao, J., Hellwich, O., Paul, M. (2019). Deep Learning Models for Retinal Blood Vessels Segmentation: A Review. IEEE Access, 7, 71696-71717. [More Information]
Song, X., Jiang, X., Gao, J., Cai, Z. (2019). Gaussian Process Graph-Based Discriminant Analysis for Hyperspectral Images Classification. Remote Sensing, 11(19), 1-21. [More Information]
Soomro, T., Afifi, A., Ali Shah, A., Soomro, S., Baloch, G., Zheng, L., Yin, M., Gao, J. (2019). Impact of Image Enhancement Technique on CNN Model for Retinal Blood Vessels Segmentation. IEEE Access, 7, 158183-158197. [More Information]
Jiang, X., Song, X., Zhang, Y., Jiang, J., Gao, J., Cai, Z. (2019). Laplacian Regularized Spatial-Aware Collaborative Graph for Discriminant Analysis of Hyperspectral Imagery. Remote Sensing, 11(1), 1-22. [More Information]
Chen, H., Li, J., Gao, J., Sun, Y., Hu, Y., Yin, B. (2019). Maximally Correlated Principal Component Analysis Based on Deep Parameterization Learning. ACM Transactions on Knowledge Discovery from Data, 13(4), 1-17. [More Information]
Yin, M., Gao, J., Xie, S., Guo, Y. (2019). Multiview Subspace Clustering via Tensorial t-Product Representation. IEEE Transactions on Neural Networks and Learning Systems, 30(3), 851-864. [More Information]
Ji, Q., Sun, Y., Gao, J., Hu, Y., Yin, B. (2019). Nonlinear Subspace Clustering via Adaptive Graph Regularized Autoencoder. IEEE Access, 7, 74122-74133. [More Information]
Ali, M., Gao, J., Antolovich, M. (2019). Parametric Classification of Bingham Distributions based on Grassmann Manifolds. IEEE Transactions on Image Processing, 28(12), 5771-5784. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2019). Probabilistic Linear Discriminant Analysis With Vectorial Representation for Tensor Data. IEEE Transactions on Neural Networks and Learning Systems, 30(10), 2938-2950. [More Information]
Zhang, H., Qian, J., Gao, J., Yang, J., Xu, C. (2019). Scalable Proximal Jacobian Iteration Method With Global Convergence Analysis for Nonconvex Unconstrained Composite Optimizations. IEEE Transactions on Neural Networks and Learning Systems, 30(9), 2825-2839. [More Information]
Chen, H., Sun, Y., Gao, J., Hu, Y., Yin, B. (2019). Solving Partial Least Squares Regression via Manifold Optimization Approaches. IEEE Transactions on Neural Networks and Learning Systems, 30(2), 588-600. [More Information]
Li, J., Huai, H., Gao, J., Kong, D., Wang, L. (2019). Spatial-temporal dynamic hand gesture recognition via hybrid deep learning model. Journal on Multimodal User Interfaces, 13(4), 363-371. [More Information]
Soomro, T., Afifi, A., Gao, J., Hellwich, O., Zheng, L., Paul, M. (2019). Strided fully convolutional neural network for boosting the sensitivity of retinal blood vessels segmentation. Expert Systems with Applications, 134, 36-52. [More Information]
Ju, F., Sun, Y., Gao, J., Antolovich, M., Dong, J., Yin, B. (2019). Tensorizing Restricted Boltzmann Machine. ACM Transactions on Knowledge Discovery from Data, 13(3), 1-16. [More Information]
Xu, C., Yang, J., Lai, H., Gao, J., Shen, L., Yan, S. (2019). UP-CNN: Un-pooling augmented convolutional neural network. Pattern Recognition Letters, 119, 34-40. [More Information]
Wu, L., Wang, Y., Gao, J., Li, X. (2019). Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification. IEEE Transactions on Multimedia, 21(6), 1412-1424. [More Information]
Hu, F., Liu, W., Tsai, S., Gao, J., Bin, N., Chen, Q. (2018). An Empirical Study on Visualizing the Intellectual Structure and Hotspots of Big Data Research from a Sustainable Perspective. Sustainability, 10(3), 1-19. [More Information]
Ali, M., Gao, J. (2018). Classification of matrix-variate Fisher-Bingham distribution via Maximum Likelihood Estimation using manifold valued data. Neurocomputing, 295, 72-85. [More Information]
Wu, L., Wang, Y., Gao, J., Li, X. (2018). Deep adaptive feature embedding with local sample distributions for person re-identification. Pattern Recognition, 73, 275-288. [More Information]
Chen, H., Sun, Y., Gao, J., Hu, Y., Yin, B. (2018). Fast optimization algorithm on Riemannian manifolds and its application in low-rank learning. Neurocomputing, 291, 59-70. [More Information]
Soomro, T., Khan, T., Khan, M., Gao, J., Paul, M., Zheng, L. (2018). Impact of ICA-Based Image Enhancement Technique on Retinal Blood Vessels Segmentation. IEEE Access, 6, 3524-3538. [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2018). Localized LRR on Grassmann Manifold: An Extrinsic View. IEEE Transactions on Circuits and Systems for Video Technology, 28(10), 2524-2536. [More Information]
Yin, M., Wu, Z., Shi, D., Gao, J., Xie, S. (2018). Locally adaptive sparse representation on Riemannian manifolds for robust classification. Neurocomputing, 310, 69-76. [More Information]
Wang, B., Hu, Y., Gao, J., Ali, M., Tien, D., Sun, Y., Yin, B. (2018). Low Rank Representation on SPD Matrices with Log-Euclidean Metric. Pattern Recognition, 76, 623-634. [More Information]
Zheng, W., Xu, C., Yang, J., Gao, J., Zhu, F. (2018). Low-rank structure preserving for unsupervised feature selection. Neurocomputing, 314, 360-370. [More Information]
Qi, N., Shi, Y., Sun, X., Wang, J., Yin, B., Gao, J. (2018). Multi-Dimensional Sparse Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(1), 163-178. [More Information]
Wang, Y., Wu, L., Lin, X., Gao, J. (2018). Multiview Spectral Clustering via Structured Low-Rank Matrix Factorization. IEEE Transactions on Neural Networks and Learning Systems, 29(10), 4833-4843. [More Information]
Zhu, F., Gao, J., Xu, C., Yang, J., Tao, D. (2018). On Selecting Effective Patterns for Fast Support Vector Regression Training. IEEE Transactions on Neural Networks and Learning Systems, 29(8), 3610-3622. [More Information]
Wang, B., Yongli, H., Gao, J., Sun, Y., Yin, B. (2018). Partial sum minimization of singular values representation on grassmann manifolds. ACM Transactions on Knowledge Discovery from Data, 12(1), 1-22. [More Information]
Zhang, Z., Xu, C., Yang, J., Gao, J., Cui, Z. (2018). Progressive Hard-Mining Network for Monocular Depth Estimation. IEEE Transactions on Image Processing, 27(8), 3691-3702. [More Information]
Yin, M., Zeng, D., Gao, J., Wu, Z., Xie, S. (2018). Robust Multinomial Logistic Regression Based on RPCA. IEEE Journal on Selected Topics in Signal Processing, 12(6), 1144-1154. [More Information]
Xu, C., Yang, J., Gao, J., Lai, H., Yan, S. (2018). SRNN: Self-regularized neural network. Neurocomputing, 273, 260-270. [More Information]
Yin, M., Xie, S., Wu, Z., Zhang, Y., Gao, J. (2018). Subspace Clustering via Learning an Adaptive Low-Rank Graph. IEEE Transactions on Image Processing, 27(8), 3716-3728. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2018). Vectorial Dimension Reduction for Tensors Based on Bayesian Inference. IEEE Transactions on Neural Networks and Learning Systems, 29(10), 4579-4592. [More Information]
Wu, L., Wang, Y., Li, X., Gao, J. (2018). What-and-where to match: Deep spatially multiplicative integration networks for person re-identification. Pattern Recognition, 76, 727-738. [More Information]
Li, F., Xin, L., Guo, Y., Gao, J., Jia, X. (2017). A Framework of Mixed Sparse Representations for Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing, 55(2), 1210-1221. [More Information]
Shi, D., Wang, J., Cheng, D., Gao, J. (2017). A global-local affinity matrix model via EigenGap for graph-based subspace clustering. Pattern Recognition Letters, 89, 67-72. [More Information]
Soomro, T., Gao, J., Khan, T., Hani, A., Khan, M., Paul, M. (2017). Computerised approaches for the detection of diabetic retinopathy using retinal fundus images: a survey. Pattern Analysis and Applications, 20(4), 927-961. [More Information]
Soomro, T., Khan, M., Gao, J., Khan, T., Paul, M. (2017). Contrast normalization steps for increased sensitivity of a retinal image segmentation method. Signal, Image and Video Processing, 11(8), 1509-1517. [More Information]
Zhu, F., Yang, J., Gao, J., Xu, C., Xu, S., Gao, C. (2017). Finding the samples near the decision plane for support vector learning. Information Sciences, 382-383, 292-307. [More Information]
Hong, X., Chen, S., Guo, Y., Gao, J. (2017). l1-norm penalised orthogonal forward regression. International Journal of Systems Science, 48(10), 2195-2201. [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2017). Laplacian LRR on Product Grassmann Manifolds for Human Activity Clustering in Multicamera Video Surveillance. IEEE Transactions on Circuits and Systems for Video Technology, 27(3), 554-566. [More Information]
Liu, Q., Shao, G., Wang, Y., Gao, J., Leung, H. (2017). Log-Euclidean Metrics for Contrast Preserving Decolorization. IEEE Transactions on Image Processing, 26(12), 5772-5783. [More Information]
Chowdhury, M., Gao, J., Islam, R. (2017). Robust human detection and localization in security applications. Concurrency and Computation: Practice and Experience, 29(23), 1-17. [More Information]
Jiang, X., Fang, X., Chen, Z., Gao, J., Jiang, J., Cai, Z. (2017). Supervised Gaussian Process Latent Variable Model for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters, 14(10), 1760-1764. [More Information]
Hong, X., Gao, J., Chen, S. (2017). Zero-Attracting Recursive Least Squares Algorithms. IEEE Transactions on Vehicular Technology, 66(1), 213-221. [More Information]
Rahman, A., Gao, J., D'Este, C., Ahmed, S. (2016). An Assessment of the Effects of Prior Distributions on the Bayesian Predictive Inference. International Journal of Statistics and Probability, 5(5), 31-42. [More Information]
Zhu, F., Yang, J., Gao, J., Xu, C. (2016). Extended nearest neighbor chain induced instance-weights for SVMs. Air Medical Journal, 60(December), 863-874. [More Information]
Sun, Y., Gao, J., Hong, X., Mishra, B., Yin, B. (2016). Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(3), 476-489. [More Information]
Yin, M., Gao, J., Lin, Z. (2016). Laplacian Regularized Low-Rank Representation and Its Applications. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(3), 504-517. [More Information]
Wang, J., Shi, D., Cheng, D., Zhang, Y., Gao, J. (2016). LRSR: Low-Rank-Sparse representation for subspace clustering. Neurocomputing, 214, 1026-1037. [More Information]
Dong, J., Gao, J., Ju, F., Shen, J. (2016). Modulus Methods for Nonnegatively Constrained Image Restoration. SIAM Journal on Imaging Sciences (SIIMS), 9(3), 1226-1246. [More Information]
Xu, C., Lu, C., Liang, X., Gao, J., Zheng, W., Wang, T., Yan, S. (2016). Multi-Loss Regularized Deep Neural Network. IEEE Transactions on Circuits and Systems for Video Technology, 26(12), 2273-2283. [More Information]
Soomro, T., Gao, J. (2016). Non-Invasive Contrast Normalisation and Denosing Technique for the Retinal Fundus Image. Annals of Data Science, 3(3), 265-279. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2016). Nonparametric tensor dictionary learning with beta process priors. Neurocomputing, 218, 120-130. [More Information]
Wu, F., Hu, Y., Gao, J., Sun, Y., Yin, B. (2016). Ordered Subspace Clustering With Block-Diagonal Priors. IEEE Transactions on Cybernetics, 46(12), 3209-3219. [More Information]
Paul, M., Xiao, R., Gao, J., Bossomaier, T. (2016). Reflectance Prediction Modelling for Residual-based Hyperspectral Image Coding. PloS One, 11(10), 1-16. [More Information]
Fu, Y., Gao, J., Tien, D., Lin, Z., Hong, X. (2016). Tensor LRR and Sparse Coding-Based Subspace Clustering. IEEE Transactions on Neural Networks and Learning Systems, 27(10), 2120-2133. [More Information]
Yin, M., Gao, J., Shi, D., Cai, S. (2015). Band-Level Correlation Noise Modeling for Wyner-Ziv Video Coding with Gaussian Mixture Models. Circuits, Systems and Signal Processing, 34(7), 2237-2254. [More Information]
Xu, C., Lu, C., Gao, J., Zheng, W., Wang, T., Yan, S. (2015). Discriminative Analysis for Symmetric Positive Definite Matrices on Lie Groups. IEEE Transactions on Circuits and Systems for Video Technology, 25(10), 1576-1585. [More Information]
Yin, M., Gao, J., Lin, Z., Shi, Q., Guo, Y. (2015). Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering. IEEE Transactions on Image Processing, 24(12), 4918-4933. [More Information]
Xu, C., Lu, C., Gao, J., Wang, T., Yan, S. (2015). Facial Analysis With a Lie Group Kernel. IEEE Transactions on Circuits and Systems for Video Technology, 25(7), 1140-1150. [More Information]
Cui, L., Ling, Z., Poon, J., Poon, S., Chen, H., Gao, J., Kwan, P., Fan, K. (2015). Generalized Gaussian reference curve measurement model for high-performance liquid chromatography with diode array detector separation and its solution by multi-target intermittent particle swarm optimization. Journal of Chemometrics, 29(3), 146-153. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2015). Image Outlier Detection and Feature Extraction via L1-Norm-Based 2D Probabilistic PCA. IEEE Transactions on Image Processing, 24(12), 4834-4846. [More Information]
Yin, M., Gao, J., Cai, S. (2015). Image super-resolution via 2D tensor regression learning. Computer Vision and Image Understanding, 132, 12-23. [More Information]
Hong, X., Chen, S., Gao, J., Harris, C. (2015). Nonlinear Identification Using Orthogonal Forward Regression With Nested Optimal Regularization. IEEE Transactions on Cybernetics, 45(12), 2925-2936. [More Information]
Yin, M., Gao, J., Guo, Y. (2015). Nonlinear low-rank representation on Stiefel manifolds. Electronics Letters, 51(10), 749-751. [More Information]
Guo, Y., Gao, J., Li, F. (2015). Random spatial subspace clustering. Knowledge-Based Systems, 74, 106-118. [More Information]
Zhang, H., Lin, Z., Zhang, C., Gao, J. (2015). Relations Among Some Low-Rank Subspace Recovery Models. Neural Computation, 27(9), 1915-1950. [More Information]
Wang, F., Sahli, H., Gao, J., Jiang, D., Verhelst, W. (2015). Relevance units machine based dimensional and continuous speech emotion prediction. Multimedia Tools and Applications, 74(22), 9983-10000. [More Information]
Hong, X., Gao, J., Chen, S., Zia, T. (2015). Sparse Density Estimation on the Multinomial Manifold. IEEE Transactions on Neural Networks and Learning Systems, 26(11), 2972-2977. [More Information]
Cui, L., Ling, Z., Poon, J., Poon, S., Gao, J., Kwan, P. (2014). A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization. Applied Computational Intelligence and Soft Computing, 2014, 1-10. [More Information]
Cui, A., Ling, Z., Poon, J., Poon, S., Chen, H., Gao, J., Kwan, P., Fan, K. (2014). A parallel model of independent component analysis constrained by a 5-parameter reference curve and its solution by multi-target particle swarm optimization. Analytical Methods, 6(8), 2679-2686. [More Information]
Cui, L., Poon, J., Poon, S., Chen, H., Gao, J., Kwan, P., Fan, K., Ling, Z. (2014). An improved independent component analysis model for 3D chromatogram separation and its solution by multi-areas genetic algorithm. BMC Bioinformatics, 15(Suppl 12), 1-10. [More Information]
Xu, C., Wang, T., Gao, J., Cao, S., Tao, W., Liu, F. (2014). An Ordered-Patch-Based Image Classification Approach on the Image Grassmannian Manifold. IEEE Transactions on Neural Networks and Learning Systems, 25(4), 728-737. [More Information]
Yin, M., Gao, J., Tien, D., Cai, S. (2014). Blind image deblurring via coupled sparse representation. Journal of Visual Communication and Image Representation, 25(5), 814-821. [More Information]
Chen, S., Hong, X., Gao, J., Harris, C. (2014). Complex-valued B-spline neural networks for modeling and inverting hammerstein systems. IEEE Transactions on Neural Networks and Learning Systems, 25(9), 1673-1685. [More Information]
Piao, X., Hu, Y., Sun, Y., Yin, B., Gao, J. (2014). Correlated Spatio-Temporal Data Collection in Wireless Sensor Networks Based on Low Rank Matrix Approximation and Optimized Node Sampling. Sensors, 14(12), 23137-23158. [More Information]
Hong, X., Gao, J., Jiang, X., Harris, C. (2014). Estimation of Gaussian process regression model using probability distance measures. Systems Science & Control Engineering, 2(1), 655-663. [More Information]
Hong, X., Gao, J., Jiang, X., Harris, C. (2014). Fast identification algorithms for Gaussian process model. Neurocomputing, 133, 25-31. [More Information]
Guo, Y., Berman, M., Gao, J. (2014). Group subset selection for linear regression. Computational Statistics and Data Analysis, 75, 39-52. [More Information]
Liu, R., Lin, Z., Su, Z., Gao, J. (2014). Linear time Principal Component Pursuit and its extensions using l1 filtering. Neurocomputing, 142, 529-541. [More Information]
Zhang, H., Lin, Z., Zhang, C., Gao, J. (2014). Robust latent low rank representation for subspace clustering. Neurocomputing, 145, 369-373. [More Information]
Guo, Y., Gao, J., Li, F. (2014). Spatial subspace clustering for drill hole spectral data. Journal of Applied Remote Sensing, 8(1), 1-19. [More Information]
Jiang, X., Gao, J., Wang, T., Shi, D. (2014). TPSLVM: A Dimensionality Reduction Algorithm Based On Thin Plate Splines. IEEE Transactions on Cybernetics, 44(10), 1795-1807. [More Information]
Tong, B., Gao, J., Nguyen Huy, T., Shao, H., Suzuki, E. (2014). Transfer dimensionality reduction by Gaussian process in parallel. Knowledge and Information Systems, 38(3), 567-597. [More Information]
Letchford, A., Gao, J., Zheng, L. (2013). Filtering financial time series by least squares. International Journal of Machine Learning and Cybernetics, 4(2), 149-154. [More Information]
Cheng, D., Nguyen, M., Gao, J., Shi, D. (2013). On the construction of the relevance vector machine based on Bayesian Ying-Yang harmony learning. Neural Networks, 48, 173-179. [More Information]
Hong, X., Gao, J., Chen, S., Harris, C. (2013). Particle swarm optimisation assisted classification using elastic net prefiltering. Neurocomputing, 122, 210-220. [More Information]
Shi, D., Gao, J., Rahmdel, P., Antolovich, M., Clark, T. (2013). UND: Unite-and-divide method in fourier and radon domains for line segment detection. IEEE Transactions on Image Processing, 22(6), 2500-2505. [More Information]
Gao, J., Shi, Q., Caetano, T. (2012). Dimensionality reduction via compressive sensing. Pattern Recognition Letters, 33(9), 1163-1170. [More Information]
Jiang, X., Gao, J., Wang, T., Zheng, L. (2012). Supervised latent linear Gaussian process latent variable model for dimensionality reduction. IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics, 42(6), 1620-1632. [More Information]
Poon, S., Poon, J., McGrane, M., Zhou, X., Kwan, P., Zhang, R., Liu, B., Gao, J., Loy, C., Chan, K., Sze, D. (2011). A novel approach in discovering significant interactions from TCM patient prescription data. International Journal of Data Mining and Bioinformatics, 5(4), 353-368. [More Information]
Kwan, P., Kameyama, K., Gao, J., Toraichi, K. (2011). Content-based Image Retrieval of Cultural Heritage Symbols by Interaction of Visual Perspectives. International Journal of Pattern Recognition and Artificial Intelligence, 25(5), 643-673. [More Information]
Kwan, P., Gao, J., Guo, Y., Kameyama, K. (2010). A learning framework for adaptive fingerprint identification using relevance feedback. International Journal of Pattern Recognition and Artificial Intelligence, 24(1), 15-38. [More Information]
Gao, J., Zhang, J., Tien, D. (2010). Relevance Units Latent Variable Model and Nonlinear Dimensionality Reduction. IEEE Transactions on Neural Networks, 21(1), 123-135. [More Information]
Gao, J., Kwan, P., Shi, D. (2010). Sparse kernel learning with LASSO and Bayesian inference algorithm. Neural Networks, 23(2), 257-264. [More Information]
Gao, J., Kwan, P., Huang, X. (2009). Comprehensive Analysis for the Local Fisher Discriminant Analysis. International Journal of Pattern Recognition and Artificial Intelligence, 23(6), 1129-1143. [More Information]
Gao, J., Kwan, P., Guo, L. (2009). Robust multivariate L1 principal component analysis and dimensionality reduction. Neurocomputing, 72(4-6), 1242-1249. [More Information]

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Conferences

Jawanpuria, P., Shi, D., Mishra, B., Gao, J. (2025). A Riemannian Approach to Ground Metric Learning for Optimal Transport. 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Zhang, Q., Sun, Y., Guo, J., Wang, S., Li, J., Gao, J., Yin, B. (2024). AutoFGNN: A Framework for Extracting All Frequency Information from Large-Scale Graphs. 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024, Piscataway, New Jersey: IEEE. [More Information]
Zhai, J., Lin, L., Shi, D., Gao, J. (2024). Bregman Graph Neural Network. 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024, Piscataway, New Jersey: IEEE. [More Information]
Cui, Z., Hu, Y., Wang, J., Gao, J., Sun, Y., Yin, B. (2024). Common-Memory Bridged Cross-Modal Adaptive Graph Embedding for Image-Text Retrieval. 2024 IEEE International Conference on Multimedia and Expo (ICME), Niagara Falls, Canada: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
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Chi, Z., Gao, J. (2024). Maximal Coding Rate Reduction for Graph Embeddings. 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024, Piscataway, New Jersey: IEEE. [More Information]
Shi, P., Gao, J. (2024). Speed-up Implicit Graph Neural Diffusion Model: A Simplified and Robust Strategy. 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Lin, L., Gao, J. (2023). A Magnetic Framelet-Based Convolutional Neural Network for Directed Graphs. 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), United States: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wu, W., Li, B., Chen, L., Gao, J., Zhang, C. (2023). A Review for Weighted MinHash Algorithms (Extended abstract). IEEE 39th International Conference on Data Engineering (ICDE), United States: IEEE. [More Information]
Li, X., Gao, J. (2023). Audioset classification with Graph Convolutional Attention model. 2023 International Joint Conference on Neural Networks (IJCNN), United States: IEEE. [More Information]
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Tang, P., Gao, J., Zhang, L., Wang, Z. (2023). Efficient and Interpretable Compressive Text Summarisation with Unsupervised Dual-Agent Reinforcement Learning. The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP), Toronto, Canada: Association for Computational Linguistics (ACL). [More Information]
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Shi, D., Han, A., Guo, Y., Gao, J. (2023). Fixed Point Laplacian Mapping: A Geometrically Correct Manifold Learning Algorithm. 2023 International Joint Conference on Neural Networks (IJCNN), United States: IEEE. [More Information]
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Han, A., Mishra, B., Jawanpuria, P., Gao, J. (2023). Learning with Symmetric Positive Definite Matrices via Generalized Bures-Wasserstein Geometry. 6th International Conference on Geometric Science of Information GSI 2023, Cham: Springer. [More Information]
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Tang, P., Hu, K., Yan, R., Zhang, L., Gao, J., Wang, Z. (2022). OTExtSum: Extractive Text Summarisation with Optimal Transport. Findings of the Association for Computational Linguistics NAACL 2022, : International Astronautical Federation, IAF. [More Information]
Gao, S., Han, A., Gao, J. (2022). Robust Denoising in Graph Neural Networks. 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022), Singapore: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Zhao, J., Sun, Y., Guo, J., Gao, J., Yin, B. (2022). Robust Graph Convolutional Clustering With Adaptive Graph Learning. 2022 International Joint Conference on Neural Networks, IJCNN, Padua, Italy: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
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Jie, R., Gao, J., Vasnev, A., Tran, M. (2021). Regularized flexible activation function combination for deep neural networks. 25th International Conference on Pattern Recognition, ICPR 2020, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Piao, X., Hu, Y., Gao, J., Sun, Y., Yang, X., Yin, B. (2021). Reweighted Non-convex Non-smooth Rank Minimization Based Spectral Clustering on Grassmann Manifold. 15th Asian Conference on Computer Vision (ACCV 2020), Kyoto: Springer Science+Business Media. [More Information]
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Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2018). Cascaded low rank and sparse representation on grassmann manifolds. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), Stockholm: International Joint Conferences on Artificial Intelligence. [More Information]
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Hu, X., Sun, Y., Gao, J., Hu, Y., Yin, B. (2018). Locality Preserving Projection Based on F-norm. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), Palo Alto: AAAI Press.
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Chowdhury, M., Gao, J., Islam, R. (2017). Biometric authentication using facial recognition. 12th EAI International Conference on Security and Privacy in Communication Networks (SecureComm 2016), Berlin, Germany: Springer Verlag. [More Information]
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Wang, Q., Gao, J., Li, H. (2017). Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering. 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
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Wang, B., Hu, Y., Gao, J., Sun, Y., Chen, H., Ali, M., Yin, B. (2017). Locality Preserving Projections for Grassmann manifold. 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne: International Joint Conferences on Artificial Intelligence. [More Information]
Zhang, Y., Shi, D., Gao, J., Cheng, D. (2017). Low-Rank-Sparse Subspace Representation for Robust Regression. 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Liu, S., Sun, Y., Hu, Y., Gao, J., Ju, F., Yin, B. (2017). Matrix variate RBM model with Gaussian distributions. The International Joint Conference on Neural Networks (IJCNN 2017), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
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Hong, X., Gao, J. (2016). A Fast Algorithm to Estimate the Square Root of Probability Density Function. AI-2016 Thirty-sixth SGAI International Conference on Artificial Intelligence: Incorporating Applications and Innovations in Intelligent Systems XXIV, Cham: Springer. [More Information]
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Khan, M., Soomro, T., Khan, T., Bailey, D., Gao, J., Mir, N. (2016). Automatic retinal vessel extraction algorithm based on contrast-sensitive schemes. 2016 International Conference on Image and Vision Computing New Zealand (IVCNZ 2016), Palmerston North: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Ali, M., Gao, J., Antolovich, M. (2016). Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chowdhury, M., Gao, J., Islam, M. (2016). Detection of Human Faces Using Neural Networks. The 23rd International Conference on Neural Information Processing (ICONIP 2016), Cham: Springer International Publishing. [More Information]
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Chowdhury, M., Gao, J., Islam, R. (2016). Fuzzy Logic Based Filtering for Image De-noising. 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chowdhury, M., Gao, J., Islam, R. (2016). Fuzzy rule based approach for face and facial feature extraction in biometric authentication. 2016 International Conference on Image and Vision Computing New Zealand (IVCNZ 2016), Palmerston North: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chowdhury, M., Gao, J., Islam, R. (2016). Human detection and localization in secure access control by analysing facial features. 11th IEEE Conference on Industrial Electronics and Applications (ICIEA 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yin, M., Guo, Y., Gao, J., He, Z., Xie, S. (2016). Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds. 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Hong, X., Gao, J. (2016). Manifold optimization for nonnegative coefficient logistic regression. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Qi, G., Sun, Y., Gao, J., Hu, Y., Li, J. (2016). Matrix Variate Restricted Boltzmann Machine. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Ju, F., Sun, Y., Gao, J., Liu, S., Hu, Y., Yin, B. (2016). Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis. 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Ali, M., Gao, J., Antolovich, M. (2016). MLE-Based Learning on Grassmann Manifolds. 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2016), Gold Coast: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Soomro, T., Gao, J. (2016). Neural Network based denoised methods for Retinal Fundus and MRI Brain Images. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Jiang, X., Song, X., Gao, J., Cai, Z., Zhang, D. (2016). Nonparametrically Guided Autoencoder with Laplace Approximation For Dimensionality Reduction. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2016). Product Grassmann Manifold Representation and Its LRR Models. 30th AAAI Conference on Artificial Intelligence (AAAI 2016), United States: AAAI Press.
Tan, M., Xiao, S., Gao, J., Xu, D., van den Hengel, A., Shi, Q. (2016). Proximal Riemannian Pursuit for Large-scale Trace-norm Minimization. 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Soomro, T., Gao, J., Khan, M., Khan, T., Paul, M. (2016). Role of Image Contrast Enhancement Technique for Ophthalmologist as Diagnostic Tool for Diabetic Retinopathy. 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2016), Gold Coast: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Tan, M., Shi, Q., van den Hengel, A., Shen, C., Gao, J., Hu, F., Zhang, Z. (2015). Learning graph structure for multi-label image classification via clique generation. The 28th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015), Boston: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2015). Low rank representation on grassmann manifolds. 12th Asian Conference on Computer Vision (ACCV 2014), Cham, Switzerland: Springer. [More Information]
Fu, Y., Gao, J., Hong, X., Tien, D. (2015). Low rank representation on riemannian manifold of symmetric positive definite matrices. 2015 SIAM International Conference on Data Mining 2015 (SDM 2015), Vancouver: SIAM Publications. [More Information]
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Tierney, S., Guo, Y., Gao, J. (2015). Selective Multi-Source Total Variation Image Restoration. 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2015), Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE).
Hong, X., Gao, J. (2015). Sparse density estimation on multinomial manifold combining local component analysis. 2015 International Joint Conference on Neural Networks (IJCNN 2015), Killarney: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Tierney, S., Gao, J., Guo, Y. (2014). Affinity pansharpening and image fusion. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yin, M., Gao, J., Sun, Y., Cai, S. (2014). Blocky artifact removal with low-rank matrix recovery. 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Sun, Y., Gao, J., Hong, X., Guo, Y., Harris, C. (2014). Dimensionality reduction assisted tensor clustering. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Shao, G., Gao, J., Wang, T., Liu, F., Shu, Y., Yang, Y. (2014). Fuzzy c-means clustering with a new regularization term for image segmentation. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Jiang, X., Gao, J., Hong, X., Cai, Z. (2014). Gaussian Processes Autoencoder for Dimensionality Reduction. 18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2014), Taiwan: Springer-Verlag. [More Information]
Shao, G., Gao, J., Wang, T., Liu, F., Shu, Y., Yang, Y. (2014). Image Segmentation Based on Spatially Coherent Gaussian Mixture Model. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Bull, G., Gao, J., Antolovich, M. (2014). Image Segmentation Using Dictionary Learning and Compressed Random Features. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Fu, Y., Gao, J., Sun, Y., Hong, X. (2014). Joint multiple dictionary learning for Tensor sparse coding. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yin, M., Guo, Y., Gao, J. (2014). Linear Subspace Learning via sparse dimension reduction. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Cui, A., Poon, J., Poon, S., Gao, J., Kwan, P., Ling, Z. (2014). Separation model of Generalized Reference Curve Measurement for HPLC-DAD and it solution by multi-target Bare Bones Particle Swarm Optimization. 2014 IEEE International Conference Bioinformatics and Biomedicine (IEEE BIBM 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Letchford, A., Gao, J., Zheng, L. (2014). Smoothing security prices. 22nd International Conference on Pattern Recognition (ICPR 2014), Stockholm: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Tierney, S., Gao, J., Guo, Y. (2014). Subspace clustering for sequential data. 27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Fu, Y., Gao, J., Tien, D., Lin, Z. (2014). Tensor LRR based subspace clustering. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Fu, Y., Gao, J., Hong, X., Tien, D. (2014). Tensor Regression Based on Linked Multiway Parameter Analysis. 14th IEEE International Conference on Data Mining (ICDM 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Tierney, S., Gao, J., Guo, Y. (2014). The W-Penalty and Its Application to Alpha Matting with Sparse Labels. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Li, F., Tang, L., Li, C., Guo, Y., Gao, J. (2013). A new super resolution method based on combined sparse representations for remote sensing imagery. Image and Signal Processing for Remote Sensing XIX, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
Guo, Y., Gao, J., Li, F. (2013). Dimensionality Reduction with Dimension Selection. 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013), Berlin: Springer. [More Information]
Guo, Y., Gao, J., Sun, Y. (2013). Endmember extraction by exemplar finder. 9th International Conference on Advanced Data Mining and Applications (ADMA 2013), Berlin: Springer. [More Information]
Tierney, S., Bull, G., Gao, J. (2013). Image Matting for Sparse User Input by Iterative Refinement. 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, Y., Gao, J., Li, F. (2013). Large scale hyperspectral data segmentation by random spatial subspace clustering. 33rd IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Cui, A., Poon, J., Poon, S., Fan, K., Chen, H., Gao, J., Kwan, P., Ling, Z. (2013). Parallel model of independent component analysis constrained by reference curves for HPLC-DAD and its solution by multi-areas genetic algorithm. 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM2013), Piscataway, United States: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Gao, J., Guo, Y., Yin, M. (2013). Restricted Boltzmann machine approach to couple dictionary training for image super-resolution. 2013 20th IEEE International Conference on Image Processing (ICIP 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yin, M., Cai, S., Gao, J. (2013). Robust face recognition via double low-rank matrix recovery for feature extraction. 2013 20th IEEE International Conference on Image Processing (ICIP 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Hong, X., Guo, Y., Chen, S., Gao, J. (2013). Sparse model construction using coordinate descent optimization. 18th International Conference on Digital Signal Processing (DSP 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Paul, M., Gao, J., Anotolovich, M. (2012). 3D motion estimation for 3D video coding. 2012 IEEE International Conference on Acoustics, Speech and Signal Processing, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Rahman, M., Islam, M., Bossomaier, T., Gao, J. (2012). CAIRAD: A co-appearance based analysis for Incorrect Records and Attribute-values Detection. 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, Y., Gao, J., Hong, X. (2012). Constrained Grouped Sparsity. The 25th Australasian Joint Conference on Artificial Intelligence (AI 2012), Heidelberg: Springer. [More Information]
Tierney, S., Gao, J. (2012). Natural image matting with total variation regularisation. International Conference on Digital Image Computing Techniques and Applications (DICTA 2012), Piscataway, New Jersey, United States of America: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Letchford, A., Gao, J., Zheng, L. (2012). Optimizing the moving average. 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE).
Gao, J., Paul, M., Liu, J. (2012). The Image Matting Method with Regularized Matte. 13th IEEE International Conference on Multimedia and Expo (ICME 2012), Piscataway, New Jersey, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Jiang, X., Gao, J., Shi, D., Wang, T. (2012). Thin Plate Spline Latent Variable Models for dimensionality reduction. 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE).
Bull, G., Gao, J. (2012). Transposed Low Rank Representation for Image Classification. International Conference on Digital Image Computing Techniques and Applications (DICTA 2012), Piscataway, New Jersey, United States of America: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Poon, S., Fan, K., Poon, J., Loy, C., Chan, K., Kuan, P., Zhou, X., Gao, J., Zhang, R., Wang, Y., et al (2011). Analysis of herbal formulation in TCM: Infertility as a case study. IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW 2011), Los Alamitos, CA, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Bull, G., Gao, J. (2011). Classification of Hand-Written Digits Using Chordiograms. 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011), Piscataway, New Jersey, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Tong, B., Gao, J., Thack, N., Suzuki, E. (2011). Gaussian Process for Dimensionality Reduction in Transfer Learning. 11th SIAM International Conference on Data Mining (SDM 2011), Mesa, AZ, USA: SIAM Publications.
Gao, J. (2011). Image Matting via Local Tangent Space Alignment. 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011), Piscataway, New Jersey, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, Y., Gao, J. (2011). Local Feature Based Tensor Kernel for Image Manifold Learning. 15th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2011, Heidelberg, Germany: Springer. [More Information]
Gao, J. (2011). Multi-task beta process sparse kernel machines. 2011 International Joint Conference on Neural Networks (IJCNN 2011), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
McGrane, M., Poon, S., Poon, J., Chan, K., Loy, C., Zhou, X., Zhang, R., Liu, B., Kwan, P., Sze, D., et al (2010). Analysis of Synergistic and Antagonistic Effects of TCM: Cases on Diabetes and Insomnia. 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops BIBMW 2010, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Zheng, L., Gao, J., He, X. (2010). Efficient character segmentation on car license plates. 11th International Conference on Control, Automation, Robotics and Vision (ICARCV 2010), Piscataway, New Jersey, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Jiang, X., Gao, J., Wang, T., Kwan, P. (2010). Learning Gradients with Gaussian Processes. 14th Pacific-Asia Conference on Advanced in Knowledge Discovery and Data Mining (PAKDD 2010), Germany: Springer. [More Information]
Poon, J., Poon, S., Yin, D., Chan, K., Loy, C., Zhou, X., Zhang, R., Liu, B., Kwan, P., Sze, D., et al (2010). Studying Herb-Herb Interaction for Insomnia through the theory of Complementarities. 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops BIBMW 2010, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

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2025

Jawanpuria, P., Shi, D., Mishra, B., Gao, J. (2025). A Riemannian Approach to Ground Metric Learning for Optimal Transport. 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wang, B., Ma, Y., Li, X., Gao, J., Hu, Y., Yin, B. (2025). Bridging the Cross-Modality Semantic Gap in Visual Question Answering. IEEE Transactions on Neural Networks and Learning Systems, 36(3), 4519-4531. [More Information]
Shi, D., Han, A., Lin, L., Guo, Y., Wang, Z., Gao, J. (2025). Design your own universe: a physics-informed agnostic method for enhancing graph neural networks. International Journal of Machine Learning and Cybernetics, 16(2), 1129-1144. [More Information]
Wang, J., Guo, J., Sun, Y., Gao, J., Wang, S., Yang, Y., Yin, B. (2025). DGNN: Decoupled Graph Neural Networks With Structural Consistency Between Attribute and Graph Embedding Representations. IEEE Transactions on Big Data, Published online: 31 October 2024. [More Information]
Shi, D., Shao, Z., Gao, J., Wang, Z., Guo, Y. (2025). Frameless Graph Knowledge Distillation. IEEE Transactions on Neural Networks and Learning Systems, Published online: 4 September 2024. [More Information]
Liu, H., Wang, B., Sun, Y., Gao, J., Li, X., Hu, Y., Yin, B. (2025). Multi-granularity Feature Interaction and Multi-region Selection based Triplet Visual Question Answering. IEEE Transactions on Big Data, Published online: 3 September 2024. [More Information]
Yang, M., Shi, D., Zheng, X., Yin, J., Gao, J. (2025). Quasi-framelets: robust graph neural networks via adaptive framelet convolution. International Journal of Machine Learning and Cybernetics, 16(2), 755-770. [More Information]
Shao, Z., Yao, X., Chen, F., Wang, Z., Gao, J. (2025). Revisiting time-varying dynamics in stock market forecasting: A multi-source sentiment analysis approach with large language model. Decision Support Systems, 190, 114362. [More Information]
Shao, Z., Wang, Z., Yao, X., Bell, M., Gao, J. (2025). ST-MambaSync: Complement the power of Mamba and Transformer fusion for less computational cost in spatial–temporal traffic forecasting. Information Fusion, 117, 102872. [More Information]
Liu, T., Hu, Y., Li, M., Yi, J., Chang, X., Gao, J., Yin, B. (2025). Tackling Real-world Complexity: Hierarchical Modeling and Dynamic Prompting for Multimodal Long Document Classification. IEEE Transactions on Circuits and Systems for Video Technology, Published online: 3 February 2025. [More Information]
Zhang, Q., Sun, Y., Wang, S., Gao, J., Hu, Y., Yin, B. (2025). Training Large-Scale Graph Neural Networks Via Graph Partial Pooling. IEEE Transactions on Big Data, 11(1), 221-233. [More Information]

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2024

Cheng, C., Zhang, L., Li, H., Cui, W., Gao, J., Cun, Y. (2024). A Deep High-Order Tensor Sparse Representation for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing, 62, 5521416. [More Information]
Yang, Y., Sun, Y., Wang, S., Gao, J., Ju, F., Yin, B. (2024). A Dual-Masked Deep Structural Clustering Network With Adaptive Bidirectional Information Delivery. IEEE Transactions on Neural Networks and Learning Systems, 35(10), 14783-14796. [More Information]
Uddin, S., Lu, H., Rahman, A., Gao, J. (2024). A novel approach for assessing fairness in deployed machine learning algorithms. Scientific Reports, 14(1), 17753. [More Information]
Zou, C., Han, A., Lin, L., Li, M., Gao, J. (2024). A Simple Yet Effective Framelet-Based Graph Neural Network for Directed Graphs. IEEE Transactions on Artificial Intelligence, 5(4), 1647-1657. [More Information]
Zhang, Q., Sun, Y., Guo, J., Wang, S., Li, J., Gao, J., Yin, B. (2024). AutoFGNN: A Framework for Extracting All Frequency Information from Large-Scale Graphs. 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024, Piscataway, New Jersey: IEEE. [More Information]
Zhang, Q., Li, J., Sun, Y., Wang, S., Gao, J., Yin, B. (2024). Beyond low-pass filtering on large-scale graphs via Adaptive Filtering Graph Neural Networks. Neural Networks, 169, 1-10. [More Information]
Zhai, J., Lin, L., Shi, D., Gao, J. (2024). Bregman Graph Neural Network. 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024, Piscataway, New Jersey: IEEE. [More Information]
Guo, K., Yin, B., Tian, D., Hu, Y., Lin, C., Qian, Z., Sun, Y., Zhou, J., Duan, X., Gao, J. (2024). CFMMC-Align: Coarse-Fine Multi-Modal Contrastive Alignment Network for Traffic Event Video Question Answering. IEEE Transactions on Circuits and Systems for Video Technology, 34(11), 10538-10550. [More Information]
Cui, Z., Hu, Y., Wang, J., Gao, J., Sun, Y., Yin, B. (2024). Common-Memory Bridged Cross-Modal Adaptive Graph Embedding for Image-Text Retrieval. 2024 IEEE International Conference on Multimedia and Expo (ICME), Niagara Falls, Canada: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, K., Tian, D., Hu, Y., Sun, Y., Qian, S., Zhou, J., Gao, J., Yin, B. (2024). Contrastive learning for traffic flow forecasting based on multi graph convolution network. IET Intelligent Transport Systems, 18(2), 290-301. [More Information]
Guo, K., Tian, D., Zhou, J., Hu, Y., Sun, Y., Yin, B., Gao, J., Qian, S. (2024). Contrastive optimized graph convolution network for traffic forecasting. Neurocomputing, 602, 128249. [More Information]
Liu, T., Hu, Y., Gao, J., Sun, Y., Yin, B. (2024). Cross-modal Multiple Granularity Interactive Fusion Network for Long Document Classification. ACM Transactions on Knowledge Discovery from Data, 18(4), 78. [More Information]
Han, A., Mishra, B., Jawanpuria, P., Gao, J. (2024). Differentially private Riemannian optimization. Machine Learning, 113(3), 1133-1161. [More Information]
Bai, M., Huang, W., Li, T., Wang, A., Gao, J., Caiafa, C., Zhao, Q. (2024). Diffusion models demand contrastive guidance for adversarial purification to advance. 41st International Conference on Machine Learning (ICML'24), Vienna Austria: JMLR. [More Information]
Lin, L., Li, Z., Li, R., Li, X., Gao, J. (2024). Diffusion models for time-series applications: a survey. Frontiers of Informaion Technology & Electronic Engineering, 25(1), 19-41. [More Information]
Shao, J., Shi, D., Han, A., Vasnev, A., Guo, Y., Gao, J. (2024). Enhancing framelet GCNs with generalized p-Laplacian regularization. International Journal of Machine Learning and Cybernetics, 15(4), 1553-1573. [More Information]
Chen, J., Chen, S., Gao, J., Huang, Z., Zhang, J., Pu, J. (2024). Exploiting Neighbor Effect: Conv-Agnostic GNN Framework for Graphs With Heterophily. IEEE Transactions on Neural Networks and Learning Systems, 35(10), 13383-13396. [More Information]
Zhou, B., Li, R., Zheng, X., Wang, Y., Gao, J. (2024). Graph Denoising with Framelet Regularizers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12), 7606-7617. [More Information]
Yang, Y., Sun, Y., Wang, S., Guo, J., Gao, J., Ju, F., Yin, B. (2024). Graph Neural Networks with Soft Association between Topology and Attribute. 38th AAAI Conference on Artificial Intelligence, AAAI 2024, Vancouver, Canada: AAAI Press. [More Information]
Liu, T., Hu, Y., Gao, J., Sun, Y., Yin, B. (2024). Hierarchical Multi-granularity Interaction Graph Convolutional Network for Long Document Classification. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 32, 1762-1775. [More Information]
Liu, T., Hu, Y., Gao, J., Sun, Y., Yin, B. (2024). Hierarchical Multi-modal Prompting Transformer for Multi-modal Long Document Classification. IEEE Transactions on Circuits and Systems for Video Technology, 34(7), 6376-6390. [More Information]
Wang, J., Cui, Z., Wang, B., Pan, S., Gao, J., Yin, B., Gao, W. (2024). IME: Integrating Multi-curvature Shared and Specific Embedding for Temporal Knowledge Graph Completion. ACM Web Conference 2024, Singapore: Association for Computing Machinery (ACM). [More Information]
Guo, J., Yin, T., Zhao, T., Zhao, J., Sun, Y., Gao, J., Wang, Y. (2024). Improved Attributed Graph Clustering with Representation and Structure Augmentation. 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Zhang, H., Gao, J., Qian, J., Yang, J., Xu, C., Zhang, B. (2024). Linear Regression Problem Relaxations Solved by Nonconvex ADMM with Convergence Analysis. IEEE Transactions on Circuits and Systems for Video Technology, 34(2), 828-838. [More Information]
Wang, J., Wang, B., Gao, J., Pan, S., Liu, T., Yin, B., Gao, W. (2024). MADE: Multicurvature Adaptive Embedding for Temporal Knowledge Graph Completion. IEEE Transactions on Cybernetics, 54(10), 5818-5831. [More Information]
Chi, Z., Gao, J. (2024). Maximal Coding Rate Reduction for Graph Embeddings. 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024, Piscataway, New Jersey: IEEE. [More Information]
He, X., Wang, B., Gao, J., Wang, Q., Hu, Y., Yin, B. (2024). Mixed-modality Clustering via Generative Graph Structure Matching. IEEE Transactions On Knowledge And Data Engineering, 36(12), 8773-8786. [More Information]
Wang, B., Wu, G., Li, X., Gao, J., Hu, Y., Yin, B. (2024). Modality Perception Learning-Based Determinative Factor Discovery for Multimodal Fake News Detection. IEEE Transactions on Neural Networks and Learning Systems, Published online: 20 September 2024. [More Information]
Wang, J., Wang, B., Gao, J., Hu, S., Hu, Y., Yin, B. (2024). Multi-Level Interaction Based Knowledge Graph Completion. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 32, 386-396. [More Information]
Liu, T., Hu, Y., Gao, J., Wang, J., Sun, Y., Yin, B. (2024). Multi-modal long document classification based on Hierarchical Prompt and Multi-modal Transformer. Neural Networks, 176, 106322. [More Information]
He, X., Wang, B., Luo, C., Gao, J., Hu, Y., Yin, B. (2024). Multi-view subspace clustering with incomplete graph information. IET Computer Vision, Published online: 17 July 2022. [More Information]
He, X., Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2024). Parallelly Adaptive Graph Convolutional Clustering Model. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 4451-4464. [More Information]
Wang, J., Wang, B., Gao, J., Li, X., Hu, Y., Yin, B. (2024). QDN: A Quadruplet Distributor Network for Temporal Knowledge Graph Completion. IEEE Transactions on Neural Networks and Learning Systems, 35(10), 14018-14030. [More Information]
Shi, D., Shao, Z., Guo, Y., Zhao, Q., Gao, J. (2024). Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and as Non-Linear Diffusion. Transactions on Machine Learning Research, 2, 1-27.
Han, A., Mishra, B., Jawanpuria, P., Gao, J. (2024). Riemannian block SPD coupling manifold and its application to optimal transport. Machine Learning, 113(4), 1595-1622. [More Information]
Shi, P., Gao, J. (2024). Speed-up Implicit Graph Neural Diffusion Model: A Simplified and Robust Strategy. 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wen, H., Chen, T., Chai, L., Sadiq, S., Gao, J., Yin, H. (2024). Variational Counterfactual Prediction under Runtime Domain Corruption. IEEE Transactions On Knowledge And Data Engineering, 36(5), 2271-2284. [More Information]

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2023

Lin, L., Gao, J. (2023). A Magnetic Framelet-Based Convolutional Neural Network for Directed Graphs. 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), United States: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wu, W., Li, B., Chen, L., Gao, J., Zhang, C. (2023). A Review for Weighted MinHash Algorithms (Extended abstract). IEEE 39th International Conference on Data Engineering (ICDE), United States: IEEE. [More Information]
Li, X., Gao, J. (2023). Audioset classification with Graph Convolutional Attention model. 2023 International Joint Conference on Neural Networks (IJCNN), United States: IEEE. [More Information]
Sun, Z., Hu, Y., Gao, Q., Jiang, H., Gao, J., Sun, Y., Yin, B. (2023). Breaking the Barrier Between Pre-training and Fine-tuning: A Hybrid Prompting Model for Knowledge-Based VQA. 31st ACM International Conference on Multimedia MM '23, Ottawa ON, Canada: Association for Computing Machinery (ACM). [More Information]
Huo, G., Zhang, Y., Gao, J., Wang, B., Hu, Y., Yin, B. (2023). CaEGCN: Cross-Attention Fusion Based Enhanced Graph Convolutional Network for Clustering. IEEE Transactions On Knowledge And Data Engineering, 35(4), 3471-3483. [More Information]
Li, Y., Bai, M., Guan, Q., Ming, Z., Liang, X., Liu, G., Gao, J. (2023). CSD-RkNN: reverse k nearest neighbors queries with conic section discriminances. International Journal of Geographical Information Science, 37(10), 2175-2204. [More Information]
Long, T., Sun, Y., Gao, J., Hu, Y., Yin, B. (2023). Domain Adaptation as Optimal Transport on Grassmann Manifolds. IEEE Transactions on Neural Networks and Learning Systems, 34(10), 7196-7209. [More Information]
Tang, P., Gao, J., Zhang, L., Wang, Z. (2023). Efficient and Interpretable Compressive Text Summarisation with Unsupervised Dual-Agent Reinforcement Learning. The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP), Toronto, Canada: Association for Computational Linguistics (ACL). [More Information]
Xiao, Y., Li, R., Vasnev, A., Gao, J. (2023). Enhanced Loss Function based on Laplacian Eigenmaps for Graph Classification. 2023 International Joint Conference on Neural Networks (IJCNN), United States: IEEE. [More Information]
Yan, K., Gao, J., Matsypura, D. (2023). FIW-GNN: A Heterogeneous Graph-Based Learning Model for Credit Card Fraud Detection. 10th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2023, Thessaloniki, Greece: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Shi, D., Han, A., Guo, Y., Gao, J. (2023). Fixed Point Laplacian Mapping: A Geometrically Correct Manifold Learning Algorithm. 2023 International Joint Conference on Neural Networks (IJCNN), United States: IEEE. [More Information]
Liang, H., Du, X., Zhu, B., Ma, Z., Chen, K., Gao, J. (2023). Graph contrastive learning with implicit augmentations. Neural Networks, 163, 156-164. [More Information]
Li, R., Li, X., Gao, S., Choy, S., Gao, J. (2023). Graph Convolution Recurrent Denoising Diffusion Model for Multivariate Probabilistic Temporal Forecasting. 19th International Conference on Advanced Data Mining and Applications (ADMA 2023), Shenyang, China: Springer. [More Information]
Chen, J., Chen, S., Bai, M., Pu, J., Zhang, J., Gao, J. (2023). Graph Decoupling Attention Markov Networks for Semisupervised Graph Node Classification. IEEE Transactions on Neural Networks and Learning Systems, 34(12), 9859-9873. [More Information]
He, X., Wang, B., Li, R., Gao, J., Hu, Y., Huo, G., Yin, B. (2023). Graph structure learning layer and its graph convolution clustering application. Neural Networks, 165, 1010-1020. [More Information]
Hu, Y., Peng, T., Guo, K., Sun, Y., Gao, J., Yin, B. (2023). Graph transformer based dynamic multiple graph convolution networks for traffic flow forecasting. IET Intelligent Transport Systems, 17(9), 1835-1845. [More Information]
Liu, T., Hu, Y., Wang, B., Sun, Y., Gao, J., Yin, B. (2023). Hierarchical Graph Convolutional Networks for Structured Long Document Classification. IEEE Transactions on Neural Networks and Learning Systems, 34(10), 8071-8085. [More Information]
Huo, G., Zhang, Y., Wang, B., Gao, J., Hu, Y., Yin, B. (2023). Hierarchical Spatio-Temporal Graph Convolutional Networks and Transformer Network for Traffic Flow Forecasting. IEEE Transactions on Intelligent Transportation Systems, 24(4), 3855-3867. [More Information]
Soomro, T., Zheng, L., Afifi, A., Ali, A., Soomro, S., Yin, M., Gao, J. (2023). Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review. IEEE Reviews in Biomedical Engineering, 16, 70-90. [More Information]
Han, A., Mishra, B., Jawanpuria, P., Gao, J. (2023). Learning with Symmetric Positive Definite Matrices via Generalized Bures-Wasserstein Geometry. 6th International Conference on Geometric Science of Information GSI 2023, Cham: Springer. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2023). Logarithmic Schatten-p Norm Minimization for Tensorial Multi-View Subspace Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(3), 3396-3410. [More Information]
Zheng, X., Zhou, B., Li, M., Wang, Y., Gao, J. (2023). MATHNET: Haar-like wavelet multiresolution analysis for graph representation learning. Knowledge-Based Systems, 273, 110609. [More Information]
Wang, J., Wang, B., Gao, J., Hu, Y., Yin, B. (2023). Multi-Concept Representation Learning for Knowledge Graph Completion. ACM Transactions on Knowledge Discovery from Data, 17(1), 11-1-11-19. [More Information]
Yang, Y., Sun, Y., Ju, F., Wang, S., Gao, J., Yin, B. (2023). Multi-graph Fusion Graph Convolutional Networks with pseudo-label supervision. Neural Networks, 158, 305-317. [More Information]
Han, A., Mishra, B., Jawanpuria, P., Gao, J. (2023). Nonconvex-nonconcave min-max optimization on Riemannian manifolds. Transactions on Machine Learning Research, , 1-33. [More Information]
Han, A., Mishra, B., Jawanpuria, P., Gao, J. (2023). Riemannian Accelerated Gradient Methods via Extrapolation. 26th International Conference on Artificial Intelligence and Statistics (AISTATS), Spain: PMLR. [More Information]
Han, A., Mishra, B., Jawanpuria, P., Kumar, P., Gao, J. (2023). Riemannian Hamiltonian Methods for Min-Max Optimization on Manifolds. SIAM Journal on Optimization, 33(3), 1797-1827. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2023). Robust discriminant analysis with feature selective projection and between-classes structural incoherence. Digital Signal Processing, 134, 103896. [More Information]
Zhou, B., Jiang, Y., Wang, Y., Liang, J., Gao, J., Pan, S., Zhang, X. (2023). Robust Graph Representation Learning for Local Corruption Recovery. ACM Web Conference 2023 (WWW '23), United States: Association for Computing Machinery (ACM). [More Information]
Wang, J., Wang, B., Gao, J., Li, X., Hu, Y., Yin, B. (2023). TDN: Triplet Distributor Network for Knowledge Graph Completion. IEEE Transactions On Knowledge And Data Engineering, 35(12), 13002-13014. [More Information]
Tang, P., Hu, K., Zhang, L., Gao, J., Luo, J., Wang, Z. (2023). TopicCAT: Unsupervised Topic-Guided Co-Attention Transformer for Extreme Multimodal Summarisation. 31st ACM International Conference on Multimedia MM '23, Ottawa ON, Canada: Association for Computing Machinery (ACM). [More Information]
Hong, X., Gao, J., Wei, H., Xiao, J., Mitchell, R. (2023). Two-step scalable spectral clustering algorithm using landmarks and probability density estimation. Neurocomputing, 519, 173-186. [More Information]
Liang, H., Gao, J. (2023). Wasserstein Adversarially Regularized Graph Autoencoder. Neurocomputing, 541, 126235. [More Information]

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2022

Ji, Q., Sun, Y., Gao, J., Hu, Y., Yin, B. (2022). A Decoder-Free Variational Deep Embedding for Unsupervised Clustering. IEEE Transactions on Neural Networks and Learning Systems, 33(10), 5681-5693. [More Information]
Wu, W., Li, B., Chen, L., Gao, J., Zhang, C. (2022). A Review for Weighted MinHash Algorithms. IEEE Transactions On Knowledge And Data Engineering, 34(6), 2553-2573. [More Information]
Guo, Z., Min, A., Yang, B., Chen, J., Li, H., Gao, J. (2022). A Sparse Oblique-Manifold Nonnegative Matrix Factorization for Hyperspectral Unmixing. IEEE Transactions on Geoscience and Remote Sensing, 60, 5508013. [More Information]
Saha, S., Gao, J., Gerlach, R. (2022). A survey of the application of graph-based approaches in stock market analysis and prediction. International Journal of Data Science and Analytics, 14(1), 1-15. [More Information]
Zhao, J., Guo, J., Sun, Y., Gao, J., Wang, S., Yin, B. (2022). Adaptive graph convolutional clustering network with optimal probabilistic graph. Neural Networks, 156, 271-284. [More Information]
Jie, R., Gao, J., Vasnev, A., Tran, M. (2022). Adaptive hierarchical hyper-gradient descent. International Journal of Machine Learning and Cybernetics, 13(12), 3785-3805. [More Information]
Yang, Y., Ju, F., Sun, Y., Gao, J., Yin, B. (2022). Adversarially regularized joint structured clustering network. Information Sciences, 615, 136-151. [More Information]
Xu, J., Zhang, B., Wang, Z., Wang, Y., Chen, F., Gao, J., Feng, D. (2022). Affective Audio Annotation of Public Speeches with Convolutional Clustering Neural Network. IEEE Transactions on Affective Computing, 13(1), 238-249. [More Information]
Guo, K., Hu, Y., Qian, Z., Sun, Y., Gao, J., Yin, B. (2022). An Optimized Temporal-Spatial Gated Graph Convolution Network for Traffic Forecasting. IEEE Intelligent Transportation Systems Magazine, 14(1), 153-162. [More Information]
Soomro, T., Zheng, L., Afifi, A., Ali, A., Yin, M., Gao, J. (2022). Artificial intelligence (AI) for medical imaging to combat coronavirus disease (COVID-19): a detailed review with direction for future research. Artificial Intelligence Review, 55(2), 1409-1439. [More Information]
Cui, Z., Hu, Y., Sun, Y., Gao, J., Yin, B. (2022). Cross-modal alignment with graph reasoning for image-text retrieval. Multimedia Tools and Applications, 81(17), 23615-23632. [More Information]
Sun, Y., Jiang, X., Hu, Y., Duan, F., Guo, K., Wang, B., Gao, J., Yin, B. (2022). Dual Dynamic Spatial-Temporal Graph Convolution Network for Traffic Prediction. IEEE Transactions on Intelligent Transportation Systems, 23(12), 23680-23693. [More Information]
Guo, K., Hu, Y., Qian, Z., Sun, Y., Gao, J., Yin, B. (2022). Dynamic Graph Convolution Network for Traffic Forecasting Based on Latent Network of Laplace Matrix Estimation. IEEE Transactions on Intelligent Transportation Systems, 23(2), 1009-1018. [More Information]
Zhou, B., Zheng, X., Wang, Y., Li, M., Gao, J. (2022). Embedding graphs on Grassmann manifold. Neural Networks, 152, 322-331. [More Information]
Zhang, C., Chen, H., Zhang, S., Xu, G., Gao, J. (2022). Geometric inductive matrix completion: A hyperbolic approach with unified message passing. Macro In Conference. [More Information]
Hu, Y., Ding, W., Liu, T., Gao, J., Sun, Y., Yin, B. (2022). Hierarchical Multiple Granularity Attention Network for Long Document Classification. 2022 International Joint Conference on Neural Networks, IJCNN, Padua, Italy: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Liang, H., Gao, J. (2022). How Neural Processes Improve Graph Link Prediction. 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Singapore: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Han, A., Gao, J. (2022). Improved Variance Reduction Methods for Riemannian Non-Convex Optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(11), 7610-7623. [More Information]
Xiao, Y., Gao, J. (2022). Kernel Matrix-based Spd Representation For Graph Learning. 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022), Singapore: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yang, J., Ma, J., Win, K., Gao, J., Yang, Z. (2022). Low-rank and sparse representation based learning for cancer survivability prediction. Information Sciences, 582, 573-592. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2022). Multi-Attribute Subspace Clustering via Auto-Weighted Tensor Nuclear Norm Minimization. IEEE Transactions on Image Processing, 31, 7191-7205. [More Information]
Zhu, F., Gao, J., Yang, J., Ye, N. (2022). Neighborhood linear discriminant analysis. Pattern Recognition, 123, 108422. [More Information]
Tang, P., Hu, K., Yan, R., Zhang, L., Gao, J., Wang, Z. (2022). OTExtSum: Extractive Text Summarisation with Optimal Transport. Findings of the Association for Computational Linguistics NAACL 2022, : International Astronautical Federation, IAF. [More Information]
Hu, X., Sun, Y., Gao, J., Hu, Y., Ju, F., Yin, B. (2022). Probabilistic Linear Discriminant Analysis Based on L1-Norm and Its Bayesian Variational Inference. IEEE Transactions on Cybernetics, 52(3), 1616-1627. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2022). Rank Consistency Induced Multiview Subspace Clustering via Low-Rank Matrix Factorization. IEEE Transactions on Neural Networks and Learning Systems, 33(7), 3157-3170. [More Information]
Gao, S., Han, A., Gao, J. (2022). Robust Denoising in Graph Neural Networks. 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022), Singapore: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Zhao, J., Sun, Y., Guo, J., Gao, J., Yin, B. (2022). Robust Graph Convolutional Clustering With Adaptive Graph Learning. 2022 International Joint Conference on Neural Networks, IJCNN, Padua, Italy: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Hu, Y., Luo, C., Gao, J., Wang, B., Sun, Y., Yin, B. (2022). Shareability-Exclusivity Representation on Product Grassmann Manifolds for Multi-camera video clustering. Journal of Visual Communication and Image Representation, 84, 103457. [More Information]
Bai, M., Chen, J., Zhao, Q., Li, C., Zhang, J., Gao, J. (2022). Tensor Neural Controlled Differential Equations. 2022 International Joint Conference on Neural Networks, IJCNN, Padua, Italy: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Long, T., Sun, Y., Gao, J., Hu, Y., Yin, B. (2022). Video Domain Adaptation based on Optimal Transport in Grassmann Manifolds. Information Sciences, 594, 151-162. [More Information]

show 27 more

2021

Piao, X., Hu, Y., Gao, J., Sun, Y., Yang, X., Yin, B. (2021). A Spectral Clustering on Grassmann Manifold via Double Low Rank Constraint. 25th International Conference on Pattern Recognition, ICPR 2020, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Ju, F., Yin, B. (2021). Adaptive Fusion of Heterogeneous Manifolds for Subspace Clustering. IEEE Transactions on Neural Networks and Learning Systems, 32(8), 3484-3497. [More Information]
Hu, Y., Song, Z., Wang, B., Gao, J., Sun, Y., Yin, B. (2021). AKM3C: Adaptive K-Multiple-Means for Multi-view Clustering. IEEE Transactions on Circuits and Systems for Video Technology, 31(11), 4214-4226. [More Information]
Cui, Z., Hu, Y., Sun, Y., Gao, J., Yin, B. (2021). Bottom-Up Progressive Semantic Alignment for Image-Text Retrieval. 28th International Conference on Neural Information Processing, ICONIP 2021, Cham: Springer Science+Business Media. [More Information]
Hu, Y., Luo, C., Wang, B., Gao, J., Sun, Y., Yin, B. (2021). Complete/incomplete multi-view subspace clustering via soft block-diagonal-induced regulariser. IEE Proceedings-Vision Image and Signal Processing, 15(8), 618-632. [More Information]
Alam, N., Gao, J., Jones, S. (2021). Corporate Failure Prediction: An Evaluation of Deep Learning vs Discrete Hazard Models. Journal of International Financial Markets, Institutions and Money, 75. [More Information]
Shi, D., Gao, J., Hong, X., Choy, S., Wang, Z. (2021). Coupling matrix manifolds assisted optimization for optimal transport problems. Machine Learning, 110(3), 533-558. [More Information]
Wu, L., Wang, Y., Gao, J., Wang, M., Zha, Z., Tao, D. (2021). Deep Coattention-Based Comparator for Relative Representation Learning in Person Re-Identification. IEEE Transactions on Neural Networks and Learning Systems, 32(2), 722-735. [More Information]
Jie, R., Gao, J. (2021). Differentiable Neural Architecture Search for High-Dimensional Time Series Forecasting. IEEE Access, 9, 20922-20932. [More Information]
Guo, Y., Tierney, S., Gao, J. (2021). Efficient sparse subspace clustering by nearest neighbour filtering. Signal Processing, 185, 108082. [More Information]
Hong, X., Gao, J. (2021). Estimating the square root of probability density function on Riemannian manifold. Expert Systems, 38(7), e12266. [More Information]
Hu, Y., Gao, F., Sun, Y., Gao, J., Yin, B. (2021). Feature Interaction Based Graph Convolutional Networks for Image-Text Retrieval. 30th International Conference on Artificial Neural Networks (ICANN 2021), Cham: Springer Nature Switzerland. [More Information]
Yang, J., Huang, G., Ma, J., Howard, S., Ciao, M., Gao, J. (2021). Fuzzy contrastive learning for online behavior analysis. 2021 IEEE CIS International Conference on Fuzzy Systems (FUZZ 2021), Luxembourg: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Hu, Y., Chen, P., Liu, T., Gao, J., Sun, Y., Yin, B. (2021). Hierarchical Attention Transformer Networks for Long Document Classification. 2021 International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, K., Hu, Y., Sun, Y., Qian, S., Gao, J., Yin, B. (2021). Hierarchical Graph Convolution Network for Traffic Forecasting. Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), Palo Alto, California: AAAI Press. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2021). Kronecker-decomposable robust probabilistic tensor discriminant analysis. Information Sciences, 561, 196-210. [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Ju, F., Yin, B. (2021). Learning Adaptive Neighborhood Graph on Grassmann Manifolds for Video/Image-Set Subspace Clustering. IEEE Transactions on Multimedia, 23, 216-227. [More Information]
Tian, S., Liu, X., Liu, M., Bian, Y., Gao, J., Yin, B. (2021). Learning the incremental warp for 3d vehicle tracking in lidar point clouds. Remote Sensing, 13(14), 2770. [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2021). Low rank representation on product grassmann manifolds for multi-view subspace clustering. 25th International Conference on Pattern Recognition, ICPR 2020, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Xu, D., Bai, M., Long, T., Gao, J. (2021). LSTM-assisted evolutionary self-expressive subspace clustering. International Journal of Machine Learning and Cybernetics, 12(10), 2777-2793. [More Information]
Zhou, B., Gao, J., Tran, M., Gerlach, R. (2021). Manifold optimization Assisted Gaussian Variational Approximation. Journal of Computational and Graphical Statistics, 30(4), 946-957. [More Information]
Wang, M., Jiang, X., Gao, J., Wang, T., Hu, C., Liu, F., Feng, Q. (2021). Minimum unbiased risk estimate based 2DPCA for color image denoising. Neurocomputing, 440, 127-144. [More Information]
Komatsu, T., Matsui, T., Gao, J. (2021). Multi-Source Domain Adaptation with Sinkhorn Barycenter. 29th European Signal Processing Conference, EUSIPCO 2021, United Kingdom: European Signal Processing Conference (EUSIPCO). [More Information]
Han, A., Mishra,, B., Jawanpuria,, P., Gao, J. (2021). On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry. NeurIPS 2021, Virtual, Online: Springer Science and Business Media Deutschland GmbH.
Guo, K., Hu, Y., Qian, Z., Liu, H., Zhang, K., Sun, Y., Gao, J., Yin, B. (2021). Optimized Graph Convolution Recurrent Neural Network for Traffic Prediction. IEEE Transactions on Intelligent Transportation Systems, 22(2), 1138-1149. [More Information]
Jie, R., Gao, J., Vasnev, A., Tran, M. (2021). Regularized flexible activation function combination for deep neural networks. 25th International Conference on Pattern Recognition, ICPR 2020, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Piao, X., Hu, Y., Gao, J., Sun, Y., Yang, X., Yin, B. (2021). Reweighted Non-convex Non-smooth Rank Minimization Based Spectral Clustering on Grassmann Manifold. 15th Asian Conference on Computer Vision (ACCV 2020), Kyoto: Springer Science+Business Media. [More Information]
Han, A., Gao, J. (2021). Riemannian Stochastic Recursive Momentum Method for non-Convex Optimization. 30th International Joint Conference on Artificial Intelligence, IJCAI 2021. International Joint Conferences on Artificial Intelligence. [More Information]
Guo, Y., Tierney, S., Gao, J. (2021). Robust Functional Manifold Clustering. IEEE Transactions on Neural Networks and Learning Systems, 32(2), 777-787. [More Information]
Yin, S., Sun, Y., Gao, J., Hu, Y., Wang, B., Yin, B. (2021). Robust Image Representation via Low Rank Locality Preserving Projection. ACM Transactions on Knowledge Discovery from Data, 15(4), 1-22. [More Information]
Zhang, B., Wang, Z., Gao, J., Rutjes, C., Nufer, K., Tao, D., Feng, D., Menzies, S. (2021). Short-term Lesion Change Detection for Melanoma Screening with Novel Siamese Neural Network. IEEE Transactions on Medical Imaging, 40(3), 840-851. [More Information]
Saha, S., Gao, J., Gerlach, R. (2021). Stock Movement Prediction on Ex-Dividend Day Using Event Specific Features and Machine Learning Techniques. 2021 International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Saha, S., Gao, J., Gerlach, R. (2021). Stock Ranking Prediction Using List-Wise Approach and Node Embedding Technique. IEEE Access, 9, 88981-88996. [More Information]
Bai, M., Zhao, Q., Gao, J. (2021). Tensorial Time Series Prediction via Tensor Neural Ordinary Differential Equations. 2021 International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Liu, T., Hu, Y., Gao, J., Sun, Y., Yin, B. (2021). Zero-shot text classification with semantically extended graph convolutional network. 25th International Conference on Pattern Recognition, ICPR 2020, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

show 32 more

2020

Zhang, C., Gao, J., Lu, Q. (2020). Cluster Developing 1-Bit Matrix Completion. 2020 International Joint Conference on Neural Networks (IJCNN), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chowdhury, M., Gao, J., Islam, R. (2020). Extracting depth information from stereo images using a fast correlation matching algorithm. International Journal of Computers and Applications, 42(8), 798-803. [More Information]
Hu, C., Gao, J., Chen, J., Jiang, D., Shu, Y. (2020). Fine-grained age estimation with multi-attention network. IEEE Access, 8, 196013-196023. [More Information]
Zhang, C., Gao, J. (2020). Hype-HAN: Hyperbolic Hierarchical Attention Network for Semantic Embedding. 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), : Springer Verlag. [More Information]
Jie, R., Gao, J., Vasnev, A., Tran, M. (2020). HyperTube: A Framework for Population-Based Online Hyperparameter Optimization with Resource Constraints. IEEE Access, 8, 69038-69057. [More Information]
Piao, X., Hu, Y., Gao, J., Sun, Y., Yang, X., Yin, B., Zhu, W., Li, G. (2020). Kernel Clustering On Symmetric Positive Definite Manifolds Via Double Approximated Low Rank Representation. 2020 IEEE International Conference on Multimedia and Expo (ICME 2020), London, UK: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Long, T., Sun, Y., Gao, J., Hu, Y., Yin, B. (2020). Locality preserving projection based on Euler representation. Journal of Visual Communication and Image Representation, 70, 102796. [More Information]
Li, J., Yan, H., Gao, J., Kong, D., Wang, L., Wang, S., Yin, B. (2020). Matrix-variate variational auto-encoder with applications to image process. Journal of Visual Communication and Image Representation, 67, 102750. [More Information]
Hong, X., Wei, H., Gao, J. (2020). Nonlinear Logistic Regression Model Based On Simplex Basis Function. 2020 International Joint Conference on Neural Networks (IJCNN), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Zhou, B., Zheng, X., Gao, J. (2020). On the Trend-corrected Variant of Adaptive Stochastic Optimization Methods. 2020 International Joint Conference on Neural Networks (IJCNN), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, J., Sun, Y., Gao, J., Hu, Y., Yin, B. (2020). Robust Adaptive Linear Discriminant Analysis with Bidirectional Reconstruction Constraint. ACM Transactions on Knowledge Discovery from Data, 14(6), 3409478. [More Information]
Ye, Y., Gao, J., Shao, Y., Li, C., Jin, Y., Hua, X. (2020). Robust support vector regression with generic quadratic nonconvex epsilon-insensitive loss. Applied Mathematical Modelling, 82, 235-251. [More Information]
Hong, X., Gao, J., Chen, S. (2020). Semi-blind joint channel estimation and data detection on sphere manifold for MIMO with high-order QAM signaling. Journal of the Franklin Institute, 357(9), 5680-5697. [More Information]
Yin, M., Huang, W., Gao, J. (2020). Shared Generative Latent Representation Learning for Multi-View Clustering. The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), Palo Alto: AAAI Press. [More Information]

show 11 more

2019

Wang, P., He, Z., Xie, K., Gao, J., Antolovich, M., Tan, B. (2019). A hybrid algorithm for low-rank approximation of nonnegative matrix factorization. Neurocomputing, 364, 129-137. [More Information]
Khan, M., Khan, T., Soomro, T., Mir, N., Gao, J. (2019). Boosting sensitivity of a retinal vessel segmentation algorithm. Pattern Analysis and Applications, 22(2), 583-599. [More Information]
Zhu, M., Shi, D., Gao, J. (2019). Branched convolutional neural networks incorporated with Jacobian deep regression for facial landmark detection. Neural Networks, 118, 127-139. [More Information]
Xu, C., Yang, J., Gao, J. (2019). Coupled-learning convolutional neural networks for object recognition. Multimedia Tools and Applications, 78(1), 573-589. [More Information]
Yates, D., Islam, M., Gao, J. (2019). DataLearner: A Data Mining and Knowledge Discovery Tool for Android Smartphones and Tablets. 15th International Conference on Advanced Data Mining and Applications (ADMA 2019), Cham: Springer. [More Information]
Wu, L., Wang, Y., Li, X., Gao, J. (2019). Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition. IEEE Transactions on Cybernetics, 49(5), 1791-1802. [More Information]
Soomro, T., Afifi, A., Zheng, L., Soomro, S., Gao, J., Hellwich, O., Paul, M. (2019). Deep Learning Models for Retinal Blood Vessels Segmentation: A Review. IEEE Access, 7, 71696-71717. [More Information]
Piao, X., Hu, Y., Gao, J., Sun, Y., Yin, B. (2019). Double Nuclear Norm Based Low Rank Representation on Grassmann Manifolds for Clustering. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Song, X., Jiang, X., Gao, J., Cai, Z. (2019). Gaussian Process Graph-Based Discriminant Analysis for Hyperspectral Images Classification. Remote Sensing, 11(19), 1-21. [More Information]
Soomro, T., Afifi, A., Ali Shah, A., Soomro, S., Baloch, G., Zheng, L., Yin, M., Gao, J. (2019). Impact of Image Enhancement Technique on CNN Model for Retinal Blood Vessels Segmentation. IEEE Access, 7, 158183-158197. [More Information]
Yates, D., Islam, Z., Gao, J. (2019). Implementation and Performance Analysis of Data-Mining Classification Algorithms on Smartphones. In R. Islam, Y. S. Koh, Y. Zhao, G. Warwick, D. Stirling, C-T. Li, Z. Islam (Eds.), Data Mining: 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised selected papers, (pp. 331-343). Singapore: Springer. [More Information]
Jiang, X., Song, X., Zhang, Y., Jiang, J., Gao, J., Cai, Z. (2019). Laplacian Regularized Spatial-Aware Collaborative Graph for Discriminant Analysis of Hyperspectral Imagery. Remote Sensing, 11(1), 1-22. [More Information]
Long, T., Gao, J., Yang, M., Hu, Y., Yin, B. (2019). Locality Preserving Projection via Deep Neural Network. 2019 International Joint Conference on Neural Networks (IJCNN 2019), Budapest: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chen, H., Li, J., Gao, J., Sun, Y., Hu, Y., Yin, B. (2019). Maximally Correlated Principal Component Analysis Based on Deep Parameterization Learning. ACM Transactions on Knowledge Discovery from Data, 13(4), 1-17. [More Information]
Seng, K., Ang, L., Liew, A., Gao, J. (2019). Multimodal Analytics for Next-Generation Big Data Technologies and Applications. Cham: Springer International Publishing. [More Information]
Yin, M., Gao, J., Xie, S., Guo, Y. (2019). Multiview Subspace Clustering via Tensorial t-Product Representation. IEEE Transactions on Neural Networks and Learning Systems, 30(3), 851-864. [More Information]
Ji, Q., Sun, Y., Gao, J., Hu, Y., Yin, B. (2019). Nonlinear Subspace Clustering via Adaptive Graph Regularized Autoencoder. IEEE Access, 7, 74122-74133. [More Information]
Ali, M., Gao, J., Antolovich, M. (2019). Parametric Classification of Bingham Distributions based on Grassmann Manifolds. IEEE Transactions on Image Processing, 28(12), 5771-5784. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2019). Probabilistic Linear Discriminant Analysis With Vectorial Representation for Tensor Data. IEEE Transactions on Neural Networks and Learning Systems, 30(10), 2938-2950. [More Information]
Soomro, T., Gao, J., Zheng, L., Afifi, A., Soomro, S., Paul, M. (2019). Retinal Blood Vessels Extraction of Challenging Images. In R. Islam, Y. S. Koh, Y. Zhao, G. Warwick, D. Stirling, C-T. Li, Z. Islam (Eds.), Data Mining: 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised selected papers, (pp. 347-359). Singapore: Springer. [More Information]
Zhang, H., Qian, J., Gao, J., Yang, J., Xu, C. (2019). Scalable Proximal Jacobian Iteration Method With Global Convergence Analysis for Nonconvex Unconstrained Composite Optimizations. IEEE Transactions on Neural Networks and Learning Systems, 30(9), 2825-2839. [More Information]
Chen, H., Sun, Y., Gao, J., Hu, Y., Yin, B. (2019). Solving Partial Least Squares Regression via Manifold Optimization Approaches. IEEE Transactions on Neural Networks and Learning Systems, 30(2), 588-600. [More Information]
Yates, D., Islam, M., Gao, J. (2019). SPAARC: A Fast Decision Tree Algorithm. In R. Islam, Y. S. Koh, Y. Zhao, G. Warwick, D. Stirling, C-T. Li, Z. Islam (Eds.), Data Mining: 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised selected papers, (pp. 43-55). Singapore: Springer. [More Information]
Xu, D., Fang, M., Hong, X., Gao, J. (2019). Sparse Least Squares Low Rank Kernel Machines. 26th International Conference on Neural Information Processing (ICONIP 2019), Cham: Springer International Publishing. [More Information]
Li, J., Huai, H., Gao, J., Kong, D., Wang, L. (2019). Spatial-temporal dynamic hand gesture recognition via hybrid deep learning model. Journal on Multimodal User Interfaces, 13(4), 363-371. [More Information]
Soomro, T., Afifi, A., Gao, J., Hellwich, O., Zheng, L., Paul, M. (2019). Strided fully convolutional neural network for boosting the sensitivity of retinal blood vessels segmentation. Expert Systems with Applications, 134, 36-52. [More Information]
Bai, M., Choy, S., Song, X., Gao, J. (2019). Tensor-Train Parameterization for Ultra Dimensionality Reduction. 10th IEEE International Conference on Big Knowledge (ICBK 2019), Cham: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Ju, F., Sun, Y., Gao, J., Antolovich, M., Dong, J., Yin, B. (2019). Tensorizing Restricted Boltzmann Machine. ACM Transactions on Knowledge Discovery from Data, 13(3), 1-16. [More Information]
Wang, B., Gao, J. (2019). Unsupervised Learning on Grassmann Manifolds for Big Data. In K. Seng, L. Ang, A. Liew, J. Gao (Eds.), Multimodal Analytics for Next-Generation Big Data Technologies and Applications, (pp. 151-180). Cham: Springer International Publishing. [More Information]
Xu, C., Yang, J., Lai, H., Gao, J., Shen, L., Yan, S. (2019). UP-CNN: Un-pooling augmented convolutional neural network. Pattern Recognition Letters, 119, 34-40. [More Information]
Wu, L., Wang, Y., Gao, J., Li, X. (2019). Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification. IEEE Transactions on Multimedia, 21(6), 1412-1424. [More Information]

show 28 more

2018

Hu, F., Liu, W., Tsai, S., Gao, J., Bin, N., Chen, Q. (2018). An Empirical Study on Visualizing the Intellectual Structure and Hotspots of Big Data Research from a Sustainable Perspective. Sustainability, 10(3), 1-19. [More Information]
Zhu, M., Shi, D., Chen, S., Gao, J. (2018). Branched convolutional neural networks for face alignment. 19th Pacific-Rim Conference on Multimedia, PCM 2018, Cham: Springer. [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2018). Cascaded low rank and sparse representation on grassmann manifolds. 27th International Joint Conference on Artificial Intelligence (IJCAI 2018), Stockholm: International Joint Conferences on Artificial Intelligence. [More Information]
Ali, M., Gao, J. (2018). Classification of matrix-variate Fisher-Bingham distribution via Maximum Likelihood Estimation using manifold valued data. Neurocomputing, 295, 72-85. [More Information]
Zhang, Y., Chandra, R., Gao, J. (2018). Cyclone Track Prediction with Matrix Neural Networks. 2018 IEEE International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wu, L., Wang, Y., Gao, J., Li, X. (2018). Deep adaptive feature embedding with local sample distributions for person re-identification. Pattern Recognition, 73, 275-288. [More Information]
Chowdhury, M., Islam, R., Gao, J. (2018). Fast and robust biometric authentication scheme using human ear. 13th EAI International Conference on Security and Privacy in Communication Networks (SecureComm 2017), Ontario: Springer. [More Information]
Chen, H., Sun, Y., Gao, J., Hu, Y., Yin, B. (2018). Fast optimization algorithm on Riemannian manifolds and its application in low-rank learning. Neurocomputing, 291, 59-70. [More Information]
Song, X., Jiang, X., Gao, J., Cai, Z., Hong, X. (2018). Functional Locality Preserving Projection for Dimensionality Reduction. 2018 IEEE International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wang, G., Kang, W., Wu, Q., Wang, Z., Gao, J. (2018). Generative Adversarial Network (GAN) Based Data Augmentation for Palmprint Recognition. 2018 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2018), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Soomro, T., Khan, T., Khan, M., Gao, J., Paul, M., Zheng, L. (2018). Impact of ICA-Based Image Enhancement Technique on Retinal Blood Vessels Segmentation. IEEE Access, 6, 3524-3538. [More Information]
Hu, X., Sun, Y., Gao, J., Hu, Y., Yin, B. (2018). Locality Preserving Projection Based on F-norm. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), Palo Alto: AAAI Press.
Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2018). Localized LRR on Grassmann Manifold: An Extrinsic View. IEEE Transactions on Circuits and Systems for Video Technology, 28(10), 2524-2536. [More Information]
Yin, M., Wu, Z., Shi, D., Gao, J., Xie, S. (2018). Locally adaptive sparse representation on Riemannian manifolds for robust classification. Neurocomputing, 310, 69-76. [More Information]
Wang, B., Hu, Y., Gao, J., Ali, M., Tien, D., Sun, Y., Yin, B. (2018). Low Rank Representation on SPD Matrices with Log-Euclidean Metric. Pattern Recognition, 76, 623-634. [More Information]
Zheng, W., Xu, C., Yang, J., Gao, J., Zhu, F. (2018). Low-rank structure preserving for unsupervised feature selection. Neurocomputing, 314, 360-370. [More Information]
Chowdhury, M., Jahan, S., Islam, R., Gao, J. (2018). Malware detection for healthcare data security. 14th International EAI Conference on Security and Privacy in Communication Networks (SecureComm 2018), Cham: Springer. [More Information]
Qi, N., Shi, Y., Sun, X., Wang, J., Yin, B., Gao, J. (2018). Multi-Dimensional Sparse Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(1), 163-178. [More Information]
Wang, Y., Wu, L., Lin, X., Gao, J. (2018). Multiview Spectral Clustering via Structured Low-Rank Matrix Factorization. IEEE Transactions on Neural Networks and Learning Systems, 29(10), 4833-4843. [More Information]
Zhu, F., Gao, J., Xu, C., Yang, J., Tao, D. (2018). On Selecting Effective Patterns for Fast Support Vector Regression Training. IEEE Transactions on Neural Networks and Learning Systems, 29(8), 3610-3622. [More Information]
Wang, B., Yongli, H., Gao, J., Sun, Y., Yin, B. (2018). Partial sum minimization of singular values representation on grassmann manifolds. ACM Transactions on Knowledge Discovery from Data, 12(1), 1-22. [More Information]
Zhang, Z., Xu, C., Yang, J., Gao, J., Cui, Z. (2018). Progressive Hard-Mining Network for Monocular Depth Estimation. IEEE Transactions on Image Processing, 27(8), 3691-3702. [More Information]
Yin, M., Zeng, D., Gao, J., Wu, Z., Xie, S. (2018). Robust Multinomial Logistic Regression Based on RPCA. IEEE Journal on Selected Topics in Signal Processing, 12(6), 1144-1154. [More Information]
Jahan, S., Chowdhury, M., Islam, R., Gao, J. (2018). Security and privacy protection for eHealth data. 4th International Conference on Future Network Systems and Security (FNSS 2018), Paris: Springer Verlag. [More Information]
Jiang, X., Gao, J., Liu, X., Cai, Z., Zhang, D., Liu, Y. (2018). Shared Deep Kernel Learning for Dimensionality Reduction. In Phung D., Tseng V., Webb G., Ho B., Ganji M., Rashidi L. (Eds.), Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, PAKDD 2018 Melbourne, VIC, Australia, June 3–6, 2018 Proceedings, Part III, (pp. 297-308). Cham: Springer. [More Information]
Xu, C., Yang, J., Gao, J., Lai, H., Yan, S. (2018). SRNN: Self-regularized neural network. Neurocomputing, 273, 260-270. [More Information]
Soomro, T., Afifi, A., Gao, J., Hellwich, O., Paul, M., Zheng, L. (2018). Strided U-Net Model: Retinal Vessels Segmentation using Dice Loss. 2018 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2018), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yin, M., Xie, S., Wu, Z., Zhang, Y., Gao, J. (2018). Subspace Clustering via Learning an Adaptive Low-Rank Graph. IEEE Transactions on Image Processing, 27(8), 3716-3728. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2018). Vectorial Dimension Reduction for Tensors Based on Bayesian Inference. IEEE Transactions on Neural Networks and Learning Systems, 29(10), 4579-4592. [More Information]
Wu, L., Wang, Y., Li, X., Gao, J. (2018). What-and-where to match: Deep spatially multiplicative integration networks for person re-identification. Pattern Recognition, 76, 727-738. [More Information]

show 27 more

2017

Li, F., Xin, L., Guo, Y., Gao, J., Jia, X. (2017). A Framework of Mixed Sparse Representations for Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing, 55(2), 1210-1221. [More Information]
Shi, D., Wang, J., Cheng, D., Gao, J. (2017). A global-local affinity matrix model via EigenGap for graph-based subspace clustering. Pattern Recognition Letters, 89, 67-72. [More Information]
Wang, P., He, Z., Xie, K., Gao, J., Antolovich, M. (2017). A Nonnegative Projection Based Algorithm for Low-Rank Nonnegative Matrix Approximation. In Derong Liu, Shengli Xie, Yuanqing Li, Dongbin Zhao, El-Sayed M. El-Alfy (Eds.), Neural Information Processing: 24th International Conference, ICONIP 2017 Guangzhou, China, November 14-18, 2017 Proceedings, Part I, (pp. 240-247). Cham: Springer. [More Information]
Zhang, Y., Gao, J. (2017). Assessing the Performance of Deep Learning Algorithms for Newsvendor Problem. In Derong Liu, Shengli Xie, Yuanqing Li, Dongbin Zhao, El-Sayed M. El-Alfy (Eds.), Neural Information Processing: 24th International Conference, ICONIP 2017 Guangzhou, China, November 14-18, 2017 Proceedings, Part I, (pp. 912-921). Cham: Springer. [More Information]
Chowdhury, M., Gao, J., Islam, R. (2017). Biometric authentication using facial recognition. 12th EAI International Conference on Security and Privacy in Communication Networks (SecureComm 2016), Berlin, Germany: Springer Verlag. [More Information]
Soomro,, T., Afifi,, A., Gao, J., Hellwich,, O., Khan,, M., Paul,, M., Zheng,, L. (2017). Boosting Sensitivity of a Retinal Vessel Segmentation Algorithm with Convolutional Neural Network. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2017), : Springer Verlag.
Soomro, T., Gao, J., Khan, T., Hani, A., Khan, M., Paul, M. (2017). Computerised approaches for the detection of diabetic retinopathy using retinal fundus images: a survey. Pattern Analysis and Applications, 20(4), 927-961. [More Information]
Soomro, T., Khan, M., Gao, J., Khan, T., Paul, M. (2017). Contrast normalization steps for increased sensitivity of a retinal image segmentation method. Signal, Image and Video Processing, 11(8), 1509-1517. [More Information]
Zhu, F., Yang, J., Gao, J., Xu, C., Xu, S., Gao, C. (2017). Finding the samples near the decision plane for support vector learning. Information Sciences, 382-383, 292-307. [More Information]
Wang, Q., Gao, J., Li, H. (2017). Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering. 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chen,, H., Sun,, Y., Gao, J., Hu,, Y., Ju,, F. (2017). L1-2DPCA Revisit via Optimization on Product Manifolds. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2017), : Springer Verlag.
Hong, X., Chen, S., Guo, Y., Gao, J. (2017). l1-norm penalised orthogonal forward regression. International Journal of Systems Science, 48(10), 2195-2201. [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2017). Laplacian LRR on Product Grassmann Manifolds for Human Activity Clustering in Multicamera Video Surveillance. IEEE Transactions on Circuits and Systems for Video Technology, 27(3), 554-566. [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Chen, H., Ali, M., Yin, B. (2017). Locality Preserving Projections for Grassmann manifold. 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne: International Joint Conferences on Artificial Intelligence. [More Information]
Liu, Q., Shao, G., Wang, Y., Gao, J., Leung, H. (2017). Log-Euclidean Metrics for Contrast Preserving Decolorization. IEEE Transactions on Image Processing, 26(12), 5772-5783. [More Information]
Zhang, Y., Shi, D., Gao, J., Cheng, D. (2017). Low-Rank-Sparse Subspace Representation for Robust Regression. 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Gao, J., Guo, Y., Wang, Z. (2017). Matrix Neural Networks. In F Cong, A Leung, Q Wei (Eds.), Advances in Neural Networks - ISNN 2017: 14th International Symposium, ISNN 2017, Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21-26, 2017, Proceedings, Part I, (pp. 313-320). Cham: Springer. [More Information]
Liu, S., Sun, Y., Hu, Y., Gao, J., Ju, F., Yin, B. (2017). Matrix variate RBM model with Gaussian distributions. The International Joint Conference on Neural Networks (IJCNN 2017), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Soomro, T., Gao, J., Paul, M., Zheng, L. (2017). Retinal blood vessel extraction method based on basic filtering schemes. 2017 IEEE International Conference on Image Processing (ICIP 2017), China: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chowdhury, M., Islam, R., Gao, J. (2017). Robust ear biometric recognition using neural network. 12th IEEE Conference on Industrial Electronics and Applications (ICIEA 2017), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chowdhury, M., Gao, J., Islam, R. (2017). Robust human detection and localization in security applications. Concurrency and Computation: Practice and Experience, 29(23), 1-17. [More Information]
Jiang, X., Fang, X., Chen, Z., Gao, J., Jiang, J., Cai, Z. (2017). Supervised Gaussian Process Latent Variable Model for Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters, 14(10), 1760-1764. [More Information]
Bai, M., Zhang, B., Gao, J. (2017). Tensorial Neural Networks and Its Application in Longitudinal Network Data Analysis. In Derong Liu, Shengli Xie, Yuanqing Li, Dongbin Zhao, El-Sayed M. El-Alfy (Eds.), Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part II, (pp. 562-571). Cham: Springer. [More Information]
Hong, X., Gao, J., Chen, S. (2017). Zero-Attracting Recursive Least Squares Algorithms. IEEE Transactions on Vehicular Technology, 66(1), 213-221. [More Information]

show 21 more

2016

Hong, X., Gao, J. (2016). A Fast Algorithm to Estimate the Square Root of Probability Density Function. AI-2016 Thirty-sixth SGAI International Conference on Artificial Intelligence: Incorporating Applications and Innovations in Intelligent Systems XXIV, Cham: Springer. [More Information]
Rahman, A., Gao, J., D'Este, C., Ahmed, S. (2016). An Assessment of the Effects of Prior Distributions on the Bayesian Predictive Inference. International Journal of Statistics and Probability, 5(5), 31-42. [More Information]
Soomro, T., Khan, M., Gao, J., Khan, T., Paul, M., Mir, N. (2016). Automatic Retinal Vessel Extraction Algorithm. 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2016), Gold Coast: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Khan, M., Soomro, T., Khan, T., Bailey, D., Gao, J., Mir, N. (2016). Automatic retinal vessel extraction algorithm based on contrast-sensitive schemes. 2016 International Conference on Image and Vision Computing New Zealand (IVCNZ 2016), Palmerston North: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Ali, M., Gao, J., Antolovich, M. (2016). Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chowdhury, M., Gao, J., Islam, M. (2016). Detection of Human Faces Using Neural Networks. The 23rd International Conference on Neural Information Processing (ICONIP 2016), Cham: Springer International Publishing. [More Information]
Chowdhury, M., Gao, J., Islam, R. (2016). Distance Measurement of Objects using Stereo Vision. 9th Hellenic Conference on Artificial Intelligence (SETN 2016), New York: Association for Computing Machinery (ACM). [More Information]
Zhu, F., Yang, J., Gao, J., Xu, C. (2016). Extended nearest neighbor chain induced instance-weights for SVMs. Air Medical Journal, 60(December), 863-874. [More Information]
Chowdhury, M., Gao, J., Islam, R. (2016). Fast stereo matching with fuzzy correlation. 11th IEEE Conference on Industrial Electronics and Applications (ICIEA 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chowdhury, M., Gao, J., Islam, R. (2016). Fuzzy Logic Based Filtering for Image De-noising. 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chowdhury, M., Gao, J., Islam, R. (2016). Fuzzy rule based approach for face and facial feature extraction in biometric authentication. 2016 International Conference on Image and Vision Computing New Zealand (IVCNZ 2016), Palmerston North: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Sun, Y., Gao, J., Hong, X., Mishra, B., Yin, B. (2016). Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(3), 476-489. [More Information]
Chowdhury, M., Gao, J., Islam, R. (2016). Human detection and localization in secure access control by analysing facial features. 11th IEEE Conference on Industrial Electronics and Applications (ICIEA 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yin, M., Guo, Y., Gao, J., He, Z., Xie, S. (2016). Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds. 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yin, M., Gao, J., Lin, Z. (2016). Laplacian Regularized Low-Rank Representation and Its Applications. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(3), 504-517. [More Information]
Wang, J., Shi, D., Cheng, D., Zhang, Y., Gao, J. (2016). LRSR: Low-Rank-Sparse representation for subspace clustering. Neurocomputing, 214, 1026-1037. [More Information]
Hong, X., Gao, J. (2016). Manifold optimization for nonnegative coefficient logistic regression. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Qi, G., Sun, Y., Gao, J., Hu, Y., Li, J. (2016). Matrix Variate Restricted Boltzmann Machine. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Ju, F., Sun, Y., Gao, J., Liu, S., Hu, Y., Yin, B. (2016). Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis. 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Ali, M., Gao, J., Antolovich, M. (2016). MLE-Based Learning on Grassmann Manifolds. 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2016), Gold Coast: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Dong, J., Gao, J., Ju, F., Shen, J. (2016). Modulus Methods for Nonnegatively Constrained Image Restoration. SIAM Journal on Imaging Sciences (SIIMS), 9(3), 1226-1246. [More Information]
Xu, C., Lu, C., Liang, X., Gao, J., Zheng, W., Wang, T., Yan, S. (2016). Multi-Loss Regularized Deep Neural Network. IEEE Transactions on Circuits and Systems for Video Technology, 26(12), 2273-2283. [More Information]
Soomro, T., Gao, J. (2016). Neural Network based denoised methods for Retinal Fundus and MRI Brain Images. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Soomro, T., Gao, J. (2016). Non-Invasive Contrast Normalisation and Denosing Technique for the Retinal Fundus Image. Annals of Data Science, 3(3), 265-279. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2016). Nonparametric tensor dictionary learning with beta process priors. Neurocomputing, 218, 120-130. [More Information]
Jiang, X., Song, X., Gao, J., Cai, Z., Zhang, D. (2016). Nonparametrically Guided Autoencoder with Laplace Approximation For Dimensionality Reduction. 2016 International Joint Conference on Neural Networks (IJCNN 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wu, F., Hu, Y., Gao, J., Sun, Y., Yin, B. (2016). Ordered Subspace Clustering With Block-Diagonal Priors. IEEE Transactions on Cybernetics, 46(12), 3209-3219. [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2016). Product Grassmann Manifold Representation and Its LRR Models. 30th AAAI Conference on Artificial Intelligence (AAAI 2016), United States: AAAI Press.
Tan, M., Xiao, S., Gao, J., Xu, D., van den Hengel, A., Shi, Q. (2016). Proximal Riemannian Pursuit for Large-scale Trace-norm Minimization. 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Paul, M., Xiao, R., Gao, J., Bossomaier, T. (2016). Reflectance Prediction Modelling for Residual-based Hyperspectral Image Coding. PloS One, 11(10), 1-16. [More Information]
Soomro, T., Gao, J., Khan, M., Khan, T., Paul, M. (2016). Role of Image Contrast Enhancement Technique for Ophthalmologist as Diagnostic Tool for Diabetic Retinopathy. 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2016), Gold Coast: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Fu, Y., Gao, J., Tien, D., Lin, Z., Hong, X. (2016). Tensor LRR and Sparse Coding-Based Subspace Clustering. IEEE Transactions on Neural Networks and Learning Systems, 27(10), 2120-2133. [More Information]

show 29 more

2015

Yin, M., Gao, J., Shi, D., Cai, S. (2015). Band-Level Correlation Noise Modeling for Wyner-Ziv Video Coding with Gaussian Mixture Models. Circuits, Systems and Signal Processing, 34(7), 2237-2254. [More Information]
Xu, C., Lu, C., Gao, J., Zheng, W., Wang, T., Yan, S. (2015). Discriminative Analysis for Symmetric Positive Definite Matrices on Lie Groups. IEEE Transactions on Circuits and Systems for Video Technology, 25(10), 1576-1585. [More Information]
Yin, M., Gao, J., Lin, Z., Shi, Q., Guo, Y. (2015). Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering. IEEE Transactions on Image Processing, 24(12), 4918-4933. [More Information]
Xu, C., Lu, C., Gao, J., Wang, T., Yan, S. (2015). Facial Analysis With a Lie Group Kernel. IEEE Transactions on Circuits and Systems for Video Technology, 25(7), 1140-1150. [More Information]
Cui, L., Ling, Z., Poon, J., Poon, S., Chen, H., Gao, J., Kwan, P., Fan, K. (2015). Generalized Gaussian reference curve measurement model for high-performance liquid chromatography with diode array detector separation and its solution by multi-target intermittent particle swarm optimization. Journal of Chemometrics, 29(3), 146-153. [More Information]
Ju, F., Sun, Y., Gao, J., Hu, Y., Yin, B. (2015). Image Outlier Detection and Feature Extraction via L1-Norm-Based 2D Probabilistic PCA. IEEE Transactions on Image Processing, 24(12), 4834-4846. [More Information]
Yin, M., Gao, J., Cai, S. (2015). Image super-resolution via 2D tensor regression learning. Computer Vision and Image Understanding, 132, 12-23. [More Information]
Tan, M., Shi, Q., van den Hengel, A., Shen, C., Gao, J., Hu, F., Zhang, Z. (2015). Learning graph structure for multi-label image classification via clique generation. The 28th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015), Boston: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Wang, B., Hu, Y., Gao, J., Sun, Y., Yin, B. (2015). Low rank representation on grassmann manifolds. 12th Asian Conference on Computer Vision (ACCV 2014), Cham, Switzerland: Springer. [More Information]
Fu, Y., Gao, J., Hong, X., Tien, D. (2015). Low rank representation on riemannian manifold of symmetric positive definite matrices. 2015 SIAM International Conference on Data Mining 2015 (SDM 2015), Vancouver: SIAM Publications. [More Information]
Guo, Y., Gao, J., Li, F., Tierney, S., Yin, M. (2015). Low rank sequential subspace clustering. 2015 International Joint Conference on Neural Networks (IJCNN 2015), Killarney: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Hong, X., Chen, S., Gao, J., Harris, C. (2015). Nonlinear Identification Using Orthogonal Forward Regression With Nested Optimal Regularization. IEEE Transactions on Cybernetics, 45(12), 2925-2936. [More Information]
Yin, M., Gao, J., Guo, Y. (2015). Nonlinear low-rank representation on Stiefel manifolds. Electronics Letters, 51(10), 749-751. [More Information]
Guo, Y., Gao, J., Li, F. (2015). Random spatial subspace clustering. Knowledge-Based Systems, 74, 106-118. [More Information]
Zhang, H., Lin, Z., Zhang, C., Gao, J. (2015). Relations Among Some Low-Rank Subspace Recovery Models. Neural Computation, 27(9), 1915-1950. [More Information]
Wang, F., Sahli, H., Gao, J., Jiang, D., Verhelst, W. (2015). Relevance units machine based dimensional and continuous speech emotion prediction. Multimedia Tools and Applications, 74(22), 9983-10000. [More Information]
Tierney, S., Guo, Y., Gao, J. (2015). Selective Multi-Source Total Variation Image Restoration. 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2015), Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE).
Hong, X., Gao, J. (2015). Sparse density estimation on multinomial manifold combining local component analysis. 2015 International Joint Conference on Neural Networks (IJCNN 2015), Killarney: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Hong, X., Gao, J., Chen, S., Zia, T. (2015). Sparse Density Estimation on the Multinomial Manifold. IEEE Transactions on Neural Networks and Learning Systems, 26(11), 2972-2977. [More Information]

show 16 more

2014

Cui, L., Ling, Z., Poon, J., Poon, S., Gao, J., Kwan, P. (2014). A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization. Applied Computational Intelligence and Soft Computing, 2014, 1-10. [More Information]
Cui, A., Ling, Z., Poon, J., Poon, S., Chen, H., Gao, J., Kwan, P., Fan, K. (2014). A parallel model of independent component analysis constrained by a 5-parameter reference curve and its solution by multi-target particle swarm optimization. Analytical Methods, 6(8), 2679-2686. [More Information]
Tierney, S., Gao, J., Guo, Y. (2014). Affinity pansharpening and image fusion. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Cui, L., Poon, J., Poon, S., Chen, H., Gao, J., Kwan, P., Fan, K., Ling, Z. (2014). An improved independent component analysis model for 3D chromatogram separation and its solution by multi-areas genetic algorithm. BMC Bioinformatics, 15(Suppl 12), 1-10. [More Information]
Xu, C., Wang, T., Gao, J., Cao, S., Tao, W., Liu, F. (2014). An Ordered-Patch-Based Image Classification Approach on the Image Grassmannian Manifold. IEEE Transactions on Neural Networks and Learning Systems, 25(4), 728-737. [More Information]
Yin, M., Gao, J., Tien, D., Cai, S. (2014). Blind image deblurring via coupled sparse representation. Journal of Visual Communication and Image Representation, 25(5), 814-821. [More Information]
Yin, M., Gao, J., Sun, Y., Cai, S. (2014). Blocky artifact removal with low-rank matrix recovery. 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Chen, S., Hong, X., Gao, J., Harris, C. (2014). Complex-valued B-spline neural networks for modeling and inverting hammerstein systems. IEEE Transactions on Neural Networks and Learning Systems, 25(9), 1673-1685. [More Information]
Piao, X., Hu, Y., Sun, Y., Yin, B., Gao, J. (2014). Correlated Spatio-Temporal Data Collection in Wireless Sensor Networks Based on Low Rank Matrix Approximation and Optimized Node Sampling. Sensors, 14(12), 23137-23158. [More Information]
Sun, Y., Gao, J., Hong, X., Guo, Y., Harris, C. (2014). Dimensionality reduction assisted tensor clustering. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Hong, X., Gao, J., Jiang, X., Harris, C. (2014). Estimation of Gaussian process regression model using probability distance measures. Systems Science & Control Engineering, 2(1), 655-663. [More Information]
Hong, X., Gao, J., Jiang, X., Harris, C. (2014). Fast identification algorithms for Gaussian process model. Neurocomputing, 133, 25-31. [More Information]
Shao, G., Gao, J., Wang, T., Liu, F., Shu, Y., Yang, Y. (2014). Fuzzy c-means clustering with a new regularization term for image segmentation. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Jiang, X., Gao, J., Hong, X., Cai, Z. (2014). Gaussian Processes Autoencoder for Dimensionality Reduction. 18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2014), Taiwan: Springer-Verlag. [More Information]
Guo, Y., Berman, M., Gao, J. (2014). Group subset selection for linear regression. Computational Statistics and Data Analysis, 75, 39-52. [More Information]
Shao, G., Gao, J., Wang, T., Liu, F., Shu, Y., Yang, Y. (2014). Image Segmentation Based on Spatially Coherent Gaussian Mixture Model. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Bull, G., Gao, J., Antolovich, M. (2014). Image Segmentation Using Dictionary Learning and Compressed Random Features. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Fu, Y., Gao, J., Sun, Y., Hong, X. (2014). Joint multiple dictionary learning for Tensor sparse coding. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yin, M., Guo, Y., Gao, J. (2014). Linear Subspace Learning via sparse dimension reduction. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Liu, R., Lin, Z., Su, Z., Gao, J. (2014). Linear time Principal Component Pursuit and its extensions using l1 filtering. Neurocomputing, 142, 529-541. [More Information]
Zhang, H., Lin, Z., Zhang, C., Gao, J. (2014). Robust latent low rank representation for subspace clustering. Neurocomputing, 145, 369-373. [More Information]
Cui, A., Poon, J., Poon, S., Gao, J., Kwan, P., Ling, Z. (2014). Separation model of Generalized Reference Curve Measurement for HPLC-DAD and it solution by multi-target Bare Bones Particle Swarm Optimization. 2014 IEEE International Conference Bioinformatics and Biomedicine (IEEE BIBM 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Letchford, A., Gao, J., Zheng, L. (2014). Smoothing security prices. 22nd International Conference on Pattern Recognition (ICPR 2014), Stockholm: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, Y., Gao, J., Li, F. (2014). Spatial subspace clustering for drill hole spectral data. Journal of Applied Remote Sensing, 8(1), 1-19. [More Information]
Tierney, S., Gao, J., Guo, Y. (2014). Subspace clustering for sequential data. 27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Fu, Y., Gao, J., Tien, D., Lin, Z. (2014). Tensor LRR based subspace clustering. 2014 International Joint Conference on Neural Networks (IJCNN 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Fu, Y., Gao, J., Hong, X., Tien, D. (2014). Tensor Regression Based on Linked Multiway Parameter Analysis. 14th IEEE International Conference on Data Mining (ICDM 2014), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Tierney, S., Gao, J., Guo, Y. (2014). The W-Penalty and Its Application to Alpha Matting with Sparse Labels. The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Jiang, X., Gao, J., Wang, T., Shi, D. (2014). TPSLVM: A Dimensionality Reduction Algorithm Based On Thin Plate Splines. IEEE Transactions on Cybernetics, 44(10), 1795-1807. [More Information]
Tong, B., Gao, J., Nguyen Huy, T., Shao, H., Suzuki, E. (2014). Transfer dimensionality reduction by Gaussian process in parallel. Knowledge and Information Systems, 38(3), 567-597. [More Information]

show 27 more

2013

Li, F., Tang, L., Li, C., Guo, Y., Gao, J. (2013). A new super resolution method based on combined sparse representations for remote sensing imagery. Image and Signal Processing for Remote Sensing XIX, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
Guo, Y., Gao, J., Li, F. (2013). Dimensionality Reduction with Dimension Selection. 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013), Berlin: Springer. [More Information]
Guo, Y., Gao, J., Sun, Y. (2013). Endmember extraction by exemplar finder. 9th International Conference on Advanced Data Mining and Applications (ADMA 2013), Berlin: Springer. [More Information]
Letchford, A., Gao, J., Zheng, L. (2013). Filtering financial time series by least squares. International Journal of Machine Learning and Cybernetics, 4(2), 149-154. [More Information]
Tierney, S., Bull, G., Gao, J. (2013). Image Matting for Sparse User Input by Iterative Refinement. 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, Y., Gao, J., Li, F. (2013). Large scale hyperspectral data segmentation by random spatial subspace clustering. 33rd IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Cheng, D., Nguyen, M., Gao, J., Shi, D. (2013). On the construction of the relevance vector machine based on Bayesian Ying-Yang harmony learning. Neural Networks, 48, 173-179. [More Information]
Cui, A., Poon, J., Poon, S., Fan, K., Chen, H., Gao, J., Kwan, P., Ling, Z. (2013). Parallel model of independent component analysis constrained by reference curves for HPLC-DAD and its solution by multi-areas genetic algorithm. 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM2013), Piscataway, United States: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Hong, X., Gao, J., Chen, S., Harris, C. (2013). Particle swarm optimisation assisted classification using elastic net prefiltering. Neurocomputing, 122, 210-220. [More Information]
Gao, J., Guo, Y., Yin, M. (2013). Restricted Boltzmann machine approach to couple dictionary training for image super-resolution. 2013 20th IEEE International Conference on Image Processing (ICIP 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Yin, M., Cai, S., Gao, J. (2013). Robust face recognition via double low-rank matrix recovery for feature extraction. 2013 20th IEEE International Conference on Image Processing (ICIP 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Hong, X., Guo, Y., Chen, S., Gao, J. (2013). Sparse model construction using coordinate descent optimization. 18th International Conference on Digital Signal Processing (DSP 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Shi, D., Gao, J., Rahmdel, P., Antolovich, M., Clark, T. (2013). UND: Unite-and-divide method in fourier and radon domains for line segment detection. IEEE Transactions on Image Processing, 22(6), 2500-2505. [More Information]

show 10 more

2012

Paul, M., Gao, J., Anotolovich, M. (2012). 3D motion estimation for 3D video coding. 2012 IEEE International Conference on Acoustics, Speech and Signal Processing, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Rahman, M., Islam, M., Bossomaier, T., Gao, J. (2012). CAIRAD: A co-appearance based analysis for Incorrect Records and Attribute-values Detection. 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, Y., Gao, J., Hong, X. (2012). Constrained Grouped Sparsity. The 25th Australasian Joint Conference on Artificial Intelligence (AI 2012), Heidelberg: Springer. [More Information]
Gao, J., Shi, Q., Caetano, T. (2012). Dimensionality reduction via compressive sensing. Pattern Recognition Letters, 33(9), 1163-1170. [More Information]
Tierney, S., Gao, J. (2012). Natural image matting with total variation regularisation. International Conference on Digital Image Computing Techniques and Applications (DICTA 2012), Piscataway, New Jersey, United States of America: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Letchford, A., Gao, J., Zheng, L. (2012). Optimizing the moving average. 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE).
Jiang, X., Gao, J., Wang, T., Zheng, L. (2012). Supervised latent linear Gaussian process latent variable model for dimensionality reduction. IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics, 42(6), 1620-1632. [More Information]
Gao, J., Paul, M., Liu, J. (2012). The Image Matting Method with Regularized Matte. 13th IEEE International Conference on Multimedia and Expo (ICME 2012), Piscataway, New Jersey, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Jiang, X., Gao, J., Shi, D., Wang, T. (2012). Thin Plate Spline Latent Variable Models for dimensionality reduction. 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE).
Bull, G., Gao, J. (2012). Transposed Low Rank Representation for Image Classification. International Conference on Digital Image Computing Techniques and Applications (DICTA 2012), Piscataway, New Jersey, United States of America: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

show 7 more

2011

Poon, S., Poon, J., McGrane, M., Zhou, X., Kwan, P., Zhang, R., Liu, B., Gao, J., Loy, C., Chan, K., Sze, D. (2011). A novel approach in discovering significant interactions from TCM patient prescription data. International Journal of Data Mining and Bioinformatics, 5(4), 353-368. [More Information]
Poon, S., Fan, K., Poon, J., Loy, C., Chan, K., Kuan, P., Zhou, X., Gao, J., Zhang, R., Wang, Y., et al (2011). Analysis of herbal formulation in TCM: Infertility as a case study. IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW 2011), Los Alamitos, CA, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Bull, G., Gao, J. (2011). Classification of Hand-Written Digits Using Chordiograms. 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011), Piscataway, New Jersey, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Kwan, P., Kameyama, K., Gao, J., Toraichi, K. (2011). Content-based Image Retrieval of Cultural Heritage Symbols by Interaction of Visual Perspectives. International Journal of Pattern Recognition and Artificial Intelligence, 25(5), 643-673. [More Information]
Abraham, J., Kwan, P., Gao, J. (2011). Fingerprint Matching using A Hybrid Shape and Orientation Descriptor. In Jucheng Yang and Loris Nanni (Eds.), State of the art in Biometrics, (pp. 25-56). Rijeka, Croatia: InTech Publishers. [More Information]
Tong, B., Gao, J., Thack, N., Suzuki, E. (2011). Gaussian Process for Dimensionality Reduction in Transfer Learning. 11th SIAM International Conference on Data Mining (SDM 2011), Mesa, AZ, USA: SIAM Publications.
Gao, J. (2011). Image Matting via Local Tangent Space Alignment. 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011), Piscataway, New Jersey, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Guo, Y., Gao, J. (2011). Local Feature Based Tensor Kernel for Image Manifold Learning. 15th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2011, Heidelberg, Germany: Springer. [More Information]
Gao, J. (2011). Multi-task beta process sparse kernel machines. 2011 International Joint Conference on Neural Networks (IJCNN 2011), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

show 6 more

2010

Kwan, P., Gao, J., Guo, Y., Kameyama, K. (2010). A learning framework for adaptive fingerprint identification using relevance feedback. International Journal of Pattern Recognition and Artificial Intelligence, 24(1), 15-38. [More Information]
McGrane, M., Poon, S., Poon, J., Chan, K., Loy, C., Zhou, X., Zhang, R., Liu, B., Kwan, P., Sze, D., et al (2010). Analysis of Synergistic and Antagonistic Effects of TCM: Cases on Diabetes and Insomnia. 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops BIBMW 2010, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Zheng, L., Gao, J., He, X. (2010). Efficient character segmentation on car license plates. 11th International Conference on Control, Automation, Robotics and Vision (ICARCV 2010), Piscataway, New Jersey, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
Jiang, X., Gao, J., Wang, T., Kwan, P. (2010). Learning Gradients with Gaussian Processes. 14th Pacific-Asia Conference on Advanced in Knowledge Discovery and Data Mining (PAKDD 2010), Germany: Springer. [More Information]
Gao, J., Zhang, J., Tien, D. (2010). Relevance Units Latent Variable Model and Nonlinear Dimensionality Reduction. IEEE Transactions on Neural Networks, 21(1), 123-135. [More Information]
Gao, J., Kwan, P., Shi, D. (2010). Sparse kernel learning with LASSO and Bayesian inference algorithm. Neural Networks, 23(2), 257-264. [More Information]
Poon, J., Poon, S., Yin, D., Chan, K., Loy, C., Zhou, X., Zhang, R., Liu, B., Kwan, P., Sze, D., et al (2010). Studying Herb-Herb Interaction for Insomnia through the theory of Complementarities. 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops BIBMW 2010, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

show 4 more

2009

Gao, J., Kwan, P., Huang, X. (2009). Comprehensive Analysis for the Local Fisher Discriminant Analysis. International Journal of Pattern Recognition and Artificial Intelligence, 23(6), 1129-1143. [More Information]
Gao, J., Kwan, P., Poon, J., Poon, S. (2009). Proceedings of the Workshop Advances and Issues in Biomedical Data Mining (AIBDM'09). Thailand: Printing House of Thammasat University - Rangsit Campus.
Gao, J., Kwan, P., Guo, L. (2009). Robust multivariate L1 principal component analysis and dimensionality reduction. Neurocomputing, 72(4-6), 1242-1249. [More Information]

Selected Grants

2020

Deep learning based time series modeling and financial forecasting, Tran M, Gao J, Gerlach R, Australian Research Council (ARC)/Discovery Projects (DP)

2015

A phone-based imaging tool to measure fruit volume to optimise harvest time, Gao J, Wine Australia/Research Grant

2013

Online Learning for Large Scale, Complex and Structured Data, Shi Q, Gao J, Australian Research Council (ARC)/Discovery Projects (DP)
Deep Learning Model for RGB-D Video Sequence and its Applications to Human Action Recognition, Gao J, National Natural Science Foundation of China (NSFC)/Research Grant
Drawbell Boulder Detection, Gao J, Mass Mining Technology 3 (MMT3)/Research Support

2012

Efficient Algorithms for Nuclear Norm Minimisation, Gao J, Charles Sturt University/Charles Sturt University Faculty Compact Grant
Using Imaging to Monitor Rock Fragmentation in a Block Caving Mine, Gao J, Charles Sturt University/Charles Sturt University Faculty Compact Grant
Image Depth Estimation, Visualisation and Quality Assessment Using Intelligent Computing, Gao J, Charles Sturt University/Charles Sturt University Research Infrastructure Block Grants (RIBG)
A Probabilistic Framework for Nonlinear Dimensionality Reduction Algorithms, Gao J, Australian Research Council (ARC)/Discovery Projects (DP)

2011

Image Texture Segmentation, Gao J, Charles Sturt University/Charles Sturt University Faculty Compact Grant
WAREIGS: Wavelet-Network-Based Augmented-Reality-Enhanced Image-Guided Surgery, Gao J, Department of Industry, Science and Resources/Australia China Science and Research Fund
Efficient Low Resolution Image Segmentation, Gao J, Charles Sturt University/Charles Sturt University Faculty Compact Grant

Professor Junbin Gao is recruiting high quality PhD students who would like to conduct research in the areas of Data Science and Machine Learning.

The University of Sydney Business School

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Professor Junbin Gao

Selected publications

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Selected Grants

2020

2015

2013

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2011