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Junbin Gao

Junbin Gao

BSc HUST; MSc HUST; PhD DUT
Professor

Rm 4085
H70 - Abercrombie Building
The University of Sydney
NSW 2006 Australia

Telephone +61 2 8627 4856
junbin.gao@sydney.edu.au

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

Bio

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.

Junbin Gao graduated from Huazhong University of Science and Technology (HUST) in 1982 with a Bachelor Degree in Computational Mathematics. He obtained his PhD from Dalian University of Technology in 1991. Between 1991 and 1993 he worked as a postdoctoral research fellow investigating wavelet applications at Wuhan University. He was appointed as an Associate Professor in July 1993 and promoted to Professor in October 1997 in Department of Mathematics of HUST. He was Guest Professor (2003-2006) in the State Key Lab of Information Engineering in Surveying, Mapping and Remote Sensing at Wuhan University, China; Guest Professor (2007-2010) in the School of Computer Science and Technology at Huazhong University of Science and Technology, China; Guest Professor (2008-2011) in the School of Computers at Guangdong University of Technology, China; and Visiting Professor (2012-2015) in Beijing Municipal Key Lab of Multimedia and Intelligent Software Technology at Beijing University of Technology.

Until recently his major research interest has been machine learning and its application in data science, image analysis, pattern recognition, Bayesian learning & inference, and numerical optimization etc. He is the author of 260 academic research papers and two books. His recent research has involved new machine learning algorithms for big data in business. Prof Gao won two research grants in Discovery Project theme from the prestigious Australian Research Council (ARC).

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.

2018

4
Journal Article/s

Wu L, Wang Y, Gao J and Lia X 2018 'Deep adaptive feature embedding with local sample distributions for person re-identification', Pattern Recognition, vol.73, pp. 275-88 [Link]

Xu C, Yang J, Gao J, Lai H and Yan S 2018 'SRNN: Self-regularized neural network', Neurocomputing, vol.273, pp. 260-70 [Link]

Qi N, Shi Y, Sun X, Wang J, Yin B and Gao J 2018 'Multi-Dimensional Sparse Models', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.40:1, pp. 163-78 [Link]

2017

2
Book Section/s

Gao J, Guo Y and Wang Z 2017 'Matrix Neural Networks' in Advances in Neural Networks - ISNN 2017 - (14th International Symposium, ISNN 2017, Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21–26, 2017, Proceedings, Part I), ed. F Cong, A Leung & Q Wei, Springer International Publishing, Cham, Switzerland, pp. 313-20 [Link]

4
Journal Article/s

Zhu F, Yang J, Gao J, Xu C, Xu S and Gao C 2017 'Finding the samples near the decision plane for support vector learning', Information Sciences, vol.382-383, pp. 292-307 [Link]

Li F, Xin L, Guo Y, Gao J and Jia X 2017 'A Framework of Mixed Sparse Representations for Remote Sensing Images', IEEE Transactions on Geoscience and Remote Sensing, vol.55:2, pp. 1210-21 [Link]

Chowdhury M, Gao J and Islam R 2017 'Robust human detection and localization in security applications', Concurrency and Computation: Practice and Experience, vol.29:23, pp. 1-17 [Link]

Hong X, Gao J and Chen S 2017 'Zero Attracting Recursive Least Squares Algorithms', IEEE Transactions on Vehicular Technology, vol.66:1, pp. 213-21 [Link]

Wang B, Hu Y, Gao J, Sun Y and Yin B 2017 'Laplacian LRR on Product Grassmann Manifolds for Human Activity Clustering in Multi-Camera Video Surveillance', IEEE Transactions on Circuits and Systems for Video Technology, vol.27:3, pp. 554-66 [Link]

Shi D, Wang J, Cheng D and Gao J 2017 'A global-local affinity matrix model via EigenGap for graph-based subspace clustering', Pattern Recognition Letters, vol.89, pp. 67-72 [Link]

Soomro TA, Khan MAU, Gao J, Khan TM and Paul M 2017 'Contrast normalization steps for increased sensitivity of a retinal image segmentation method', Signal, Image and Video Processing, vol.11:8, pp. 1509-17 [Link]

Hong X, Chen S, Guo Y and Gao J 2017 'l1-norm penalised orthogonal forward regression', International Journal of Systems Science, vol.48:10, pp. 2195-201 [Link]

Wang B, Hu Y, Gao J, Ali M, Tien D, Sun Y and Yin B 2017 Forthcoming 'Low Rank Representation on SPD Matrices with Log-Euclidean Metric', Pattern Recognition [Link]

Soomro TA, Gao J, Khan T, Hani AFM, Khan MAU and Paul M 2017 'Computerised approaches for the detection of diabetic retinopathy using retinal fundus images: a survey', Pattern Analysis and Applications, vol.20:4, pp. 927–961 [Link]

Zhu F, Gao J, Xu C, Yang J and Tao D 2017 Forthcoming 'On Selecting Effective Patterns for Fast Support Vector Regression Training', IEEE Transactions on Neural Networks and Learning Systems [Link]

Liu Q, Shao G, Wang Y, Gao J and Leung H 2017 'Log-Euclidean Metrics for Contrast Preserving Decolorization', IEEE Transactions on Image Processing, vol.26:12, pp. 5772-83 [Link]

Ju F, Sun Y, Gao J, Hu Y and Yin B 2017 Forthcoming 'Vectorial Dimension Reduction for Tensors Based on Bayesian Inference', IEEE Transactions on Neural Networks and Learning Systems [Link]

6
Conference Proceeding/s

Wang B, Hu Y, Gao J, Sun Y, Chen H, Ali M and Yin B 2017 'Locality Preserving Projections for Grassmann manifold', Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, 25th August 2017 [Link]

Zhang Y, Shi D, Gao J and Cheng D 2017 'Low-Rank-Sparse Subspace Representation for Robust Regression', Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, Honolulu, United States, 25th July 2017

Wang Q, Gao J and Li H 2017 'Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering', Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, Honolulu, United States, 25th July 2017

Liu S, Sun Y, Hu Y, Gao J, Ju F and Yin B 2017 'Matrix variate RBM model with Gaussian distributions', Proceedings of International Joint Conference on Neural Networks (IJCNN), Anchorage, Alaska, United States, 19th May 2017 [Link]

2016

4
Journal Article/s

Wu F, Hu Y, Gao J, Sun Y and Yin B 2016 'Ordered Subspace Clustering With Block-Diagonal Priors', IEEE Transactions on Cybernetics, vol.46:12, pp. 3209-19 [Link]

Xu C, Lu C, Liang X, Gao J, Zheng W, Wang T and Yan S 2016 'Multi-loss Regularized Deep Neural Network', IEEE Transactions on Circuits and Systems for Video Technology, vol.26:2, pp. 2273-83 [Link]

Yin M, Gao J and Lin Z 2016 'Laplacian Regularized Low-Rank Representation and Its Applications', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.38:3, pp. 504-17 [Link]

Sun Y, Gao J, Hong X, Mishra B and Yin B 2016 'Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.38:3, pp. 476-89 [Link]

Fu Y, Gao J, Tien D and Lin Z 2016 'Tensor LRR and Sparse Coding-Based Subspace Clustering', IEEE Transactions on Neural Networks and Learning Systems, vol.27:10, pp. 2120-33 [Link]

Soomro TA and Gao J 2016 'Non-Invasive Contrast Normalisation and Denosing Technique for the Retinal Fundus Image', Annals of Data Science, vol.3:3, pp. 265-79 [Link]

Dong J, Gao J, Ju F and Shen J 2016 'Modulus Methods for Nonnegatively Constrained Image Restoration', SIAM Journal on Imaging Sciences, vol.9:3, pp. 1226-46 [Link]

Paul M, Xiao R, Gao J and Bossomaier T 2016 'Reflectance Prediction Modelling for Residual-based Hyperspectral Image Coding', PLOS One, vol.10:11, pp. 1-16 [Link]

Wang J, Shi D, Cheng D, Zhang Y and Gao J 2016 'LRSR: Low-Rank-Sparse representation for subspace clustering', Neurocomputing, vol.214, pp. 1026-37 [Link]

Zhu F, Yang J, Gao J and Xu C 2016 'Extended nearest neighbor chain induced instance-weights for SVMs', Pattern Recognition, vol.60, pp. 863-74 [Link]

Ju F, Sun Y, Gao J, Hu Y and Yin B 2016 'Nonparametric tensor dictionary learning with beta process priors', Neurocomputing, vol.218, pp. 120-30 [Link]

5
Conference Paper/s

Gao J and Islam R 2016 'Biometric Authentication using Facial Recognition', 12th EAI International Conference on Security and Privacy in Communication Networks, Guangzhou, China, 12th October 2016

6
Conference Proceeding/s

Hong X and 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, Cambridge, United Kingdom, 15th December 2016 [Link]

Soomro TA, Gao J, Khan MAU, Khan TM and Paul M 2016 'Role of Image Contrast Enhancement Technique for Ophthalmologist as Diagnostic Tool for Diabetic Retinopathy', Proceeding of the 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Gold Coast, Australia, 2nd December 2016

Ali M, Gao J and Antolovich M 2016 'MLE-Based Learning on Grassmann Manifolds', Proceeding of the 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Gold Coast, Australia, 2nd December 2016

Soomro TA, Khan MAU, Gao J, Khan TM, Paul M and Mir N 2016 'Automatic Retinal Vessel Extraction Algorithm', Proceeding of the 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Gold Coast, Australia, 2nd December 2016

Khan MAU, Soomro TA, Khan TM, Bailey DG, Gao J and Mir N 2016 'Automatic retinal vessel extraction algorithm based on contrast-sensitive schemes', Proceedings of the Image and Vision Computing New Zealand IVCNZ 2016, Palmerston North, New Zealand, 22nd November 2016

Chowdhury M, Gao J and Islam R 2016 'Fuzzy rule based approach for face and facial feature extraction in biometric authentication', Proceedings of the Image and Vision Computing New Zealand IVCNZ 2016, Palmerston North, New Zealand, 22nd November 2016

Chowdhury MM, Gao J and Islam MDR 2016 'Detection of Human Faces Using Neural Networks', 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part II, Kyoto, Japan, 21st October 2016 [Link]

Chowdhury MM, Gao J and Islam R 2016 'Fuzzy Logic Based Filtering for Image De-noising', 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), Vancouver, Canada, 29th July 2016 [Link]

Jiang X, Song X, Gao J, Cai Z and Zhang D 2016 'Nonparametrically Guided Autoencoder with Laplace Approximation For Dimensionality Reduction', 2016 International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada, 29th July 2016 [Link]

Qi G, Sun Y, Gao J, Hu Y and Li J 2016 'Matrix Variate Restricted Boltzmann Machine', 2016 International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada, 29th July 2016 [Link]

Soomro TA and Gao J 2016 'Neural Network based denoised methods for Retinal Fundus and MRI Brain Images', 2016 International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada, 29th July 2016 [Link]

Ali M, Gao J and 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), Vancouver, Canada, 29th July 2016 [Link]

Hong X and Gao J 2016 'Manifold optimization for nonnegative coefficient logistic regression', 2016 International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada, 29th July 2016 [Link]

Tan M, Xiao S, Gao J, Xu D, Van Den Hengel A and Shi Q 2016 'Proximal Riemannian Pursuit for Large-scale Trace-norm Minimization', Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, United States, 1st July 2016

Ju F, Sun Y, Gao J, Liu S, Hu Y and Yin B 2016 'Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis', Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, United States, 1st July 2016

Yin M, Guo Y, Gao J, He Z and Xie S 2016 'Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds', Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, United States, 1st July 2016

Chowdhury M, Gao J and Islam R 2016 'Human detection and localization in secure access control by analysing facial features', Proceedings of 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA), Hefei, China, 7th June 2016 [Link]

Chowdhury M, Gao J and Islam R 2016 'Fast stereo matching with fuzzy correlation', Proceedings of 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA), Hefei, China, 7th June 2016 [Link]

Chowdhury M, Gao J and Islam R 2016 'Distance Measurement of Objects using Stereo Vision', Proceedings of the 9th Hellenic Conference on Artificial Intelligence, Thessaloniki, Greece, 20th May 2016 [Link]

Wang B, Hu Y, Gao J, Sun Y and Yin B 2016 'Product Grassmann Manifold Representation and Its LRR Models', Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, United States, 17th February 2016

2015

4
Journal Article/s

Yin M, Gao J, Shi D and Cai S 2015 'Band-Level Correlation Noise Modeling for Wyner–Ziv Video Coding with Gaussian Mixture Models', Circuits, Systems, and Signal Processing, vol.34:7, pp. 2237-2254 [Link]

Xu C, Lu C, Gao J, Wang T and Yan S 2015 'Discriminative Analysis for Symmetric Positive Definite Matrices on Lie Groups', IEEE Transactions on Circuits and Systems for Video Technology, vol.25:10, pp. 1576-1585 [Link]

Yin M, Gao J, Lin Z, Shi Q and Guo Y 2015 'Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering', IEEE Transactions on Image Processing, vol.24:12, pp. 4918-4933 [Link]

Xu C, Lu C, Gao J, Ni B and Yan S 2015 'Facial Analysis With a Lie Group Kernel', IEEE Transactions on Circuits and Systems for Video Technology, vol.25:7, pp. 1140-1150 [Link]

Cui L, Ling Z, Poon J, Poon S, Chen H, Gao J, Kwan P and 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, vol.29:3, pp. 146-153 [Link]

Ju F, Sun Y, Gao J and Hu Y 2015 'Image Outlier Detection and Feature Extraction via L1-Norm-Based 2D Probabilistic PCA', IEEE Transactions on Image Processing, vol.24:12, pp. 4834-4846 [Link]

Yin M, Gao J and Cai S 2015 'Image super-resolution via 2D tensor regression learning', Computer Vision and Image Understanding, vol.132, pp. 12–23 [Link]

Hong X, Chen S, Gao J and Harris CJ 2015 'Nonlinear Identification Using Orthogonal Forward Regression With Nested Optimal Regularization', IEEE Transactions on Cybernetics, vol.45:12, pp. 2925-2936 [Link]

Yin M, Gao J and Guo Y 2015 'Nonlinear low-rank representation on Stiefel manifolds', Electronics Letters, vol.51:10, pp. 749-751 [Link]

Guo Y, Gao J and Li F 2015 'Random spatial subspace clustering', Knowledge-Based Systems, vol.74, pp. 106–118 [Link]

Zhang H, Lin Z, Zhang C and Gao J 2015 'Relations Among Some Low-Rank Subspace Recovery Models', Neural Computation, vol.27:9, pp. 1915-1950 [Link]

Wang F, Sahli H, Gao J, Jiang D and Verhelst W 2015 'Relevance units machine based dimensional and continuous speech emotion prediction', Multimedia Tools and Applications, vol.74:22, pp. 9983-10000 [Link]

Hong X, Gao J, Chen S and Zia T 2015 'Sparse Density Estimation on the Multinomial Manifold', IEEE Transactions on Neural Networks and Learning Systems, vol.26:11, pp. 2972-2977 [Link]

5
Conference Paper/s

Chowdhury M, Gao J and Islam R 2015 'Human Surveillance System for Security Applications', 11th EAI International Conference on Security and Privacy in Communication Networks, Dallas, United States, 29th October 2015

Chowdhury M, Gao J and Islam R 2015 'Image Spam Classification using Neural Network', 11th EAI International Conference on Security and Privacy in Communication Networks, Dallas, United States, 29th October 2015

6
Conference Proceeding/s

Guo Y, Gao J, Tierney S, Li F and Yin M 2015 'Low Rank Sequential Subspace Clustering', International Joint Conference on Neural Networks (IJCNN), Killarney, United States, 17th July 2015 [Link]

Hong X and Gao J 2015 'Sparse density estimation on multinomial manifold combining local component analysis', International Joint Conference on Neural Networks (IJCNN), Killarney, United States, 17th July 2015 [Link]

Tan M, Shi J, van den Hengel A, Shen C, Gao J and Zhang Z 2015 'Learning graph structure for multi-label image classification via clique generation', IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, United States, 12th June 2015 [Link]

Fu Y, Gao J, Hong X and Tien D 2015 'Low Rank Representation on Riemannian Manifold of Symmetric Positive Definite Matrices', Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, Canada, 2nd May 2015 [Link]

2014

4
Journal Article/s

Cui L, Ling Z, Poon J, Poon S, Chen H, Gao J, Kwan P and 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, vol.6:8, pp. 2679-2686 [Link]

Cui L, Poon J, Poon SK, Chen H, Gao J, Kwan P, Fan K and Ling Z 2014 'An improved independent component analysis model for 3D chromatogram separation and its solution by multi-areas genetic algorithm', BMC Bioinformatics, vol.15:Suppl 12, pp. 1-10 [Link]

Xu C, Wang T, Gao J, Cao S, Tao W and Liu F 2014 'An Ordered-patch Based Image Classification Approach on the Image Grassmannian Manifold', IEEE Transactions on Neural Networks and Learning Systems, vol.25:4, pp. 728-737 [Link]

Yin M, Gao J, Tien D and Cai S 2014 'Blind image deblurring via coupled sparse representation', Journal of Visual Communication and Image Representation, vol.25:5, pp. 814–821 [Link]

Piao X, Hu Y, Sun Y, Yin B and Gao J 2014 'Correlated Spatio-Temporal Data Collection in Wireless Sensor Networks Based on Low Rank Matrix Approximation and Optimized Node Sampling', Sensors, vol.14:12, pp. 23137-23158 [Link]

Hong X, Gao J, Jiang X and Harris C 2014 'Estimation of Gaussian process regression model using probability distance measures', Systems Science & Control Engineering, vol.2:1, pp. 655-663 [Link]

Hong X, Gao J, Jiang X and Harris C 2014 'Fast identification algorithms for Gaussian process model', Neurocomputing, vol.133, pp. 25–31 [Link]

Guo Y, Berman M and Gao J 2014 'Group subset selection for linear regression', Computational Statistics & Data Analysis, vol.75, pp. 39-52 [Link]

Liu R, Lin Z, Su Z and Gao J 2014 'Linear time Principal Component Pursuit and its extensions using ℓ1 filtering', Neurocomputing, vol.142, pp. 529–541 [Link]

Zhang H, Lin Z, Zhang C and Gao J 2014 'Robust latent low rank representation for subspace clustering', Neurocomputing, vol.145, pp. 369–373 [Link]

Guo Y, Gao J and Li F 2014 'Spatial subspace clustering for drill hole spectral data', Journal of Applied Remote Sensing, vol.8:1, pp. 1-19 [Link]

Jiang X, Gao J, Shi D and Wang T 2014 'TPSLVM: A Dimensionality Reduction Algorithm Based On Thin Plate Splines', IEEE Transactions on Cybernetics, vol.44:10, pp. 1795-1807 [Link]

Tong B, Gao J, Thach NH, Shao H and Suzuki E 2014 'Transfer Dimensionality Reduction by Gaussian Process in Parallel', Knowledge and Information Systems, vol.38:3, pp. 567-597 [Link]

6
Conference Proceeding/s

Fu Y, Gao J, Hong X and Tien D 2014 'Tensor Regression Based on Linked Multiway Parameter Analysis', IEEE International Conference on Data Mining (ICDM), Shenzhen, China, 17th December 2014 [Link]

Tierney S, Gao J and Guo Y 2014 'Affinity Pansharpening and Image Fusion', Proceedings of Digital lmage Computing: Techniques and Applications (DlCTA) Conference, Wollongong, Australia, 27th November 2014 [Link]

Shao G, Gao J, Wang T and Shu Y 2014 'Image Segmentation Based on Spatially Coherent Gaussian Mixture Model', Proceedings of Digital lmage Computing: Techniques and Applications (DlCTA) Conference, Wollongong, Australia, 27th November 2014 [Link]

Bull G, Gao J and Antolovich M 2014 'Image Segmentation Using Dictionary Learning and Compressed Random Features', Proceedings of Digital lmage Computing: Techniques and Applications (DlCTA) Conference, Wollongong, Australia, 27th November 2014 [Link]

Tierney S, Gao J and Guo Y 2014 'The W-Penalty and Its Application to Alpha Matting with Sparse Labels', Proceedings of Digital lmage Computing: Techniques and Applications (DlCTA) Conference, Wollongong, Australia, 27th November 2014 [Link]

Wang B, Hu Y, Gao J, Sun Y and Yin B 2014 'Low Rank Representation on Grassmann Manifolds', Proceedings of 12th Asian Conference on Computer Vision (ACCV), Singapore, Singapore, 5th November 2014 [Link]

Letchford A, Gao J and Zheng L 2014 'Smoothing Security Prices', Proceedings of International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, 28th August 2014 [Link]

Gao J, Hong X, Sun Y, Guo Y and Harris CJ 2014 'Dimensionality reduction assisted tensor clustering', International Joint Conference on Neural Networks (IJCNN), Beijing, China, 11th July 2014 [Link]

Shao G, Gao J, Wang T, Liu F, Yang Y and Shu Y 2014 'Fuzzy c-means clustering with a new regularization term for image segmentation', International Joint Conference on Neural Networks (IJCNN), Beijing, China, 11th July 2014 [Link]

Fu Y, Gao J, Sun Y and Hong X 2014 'Joint multiple dictionary learning for Tensor sparse coding', International Joint Conference on Neural Networks (IJCNN), Beijing, China, 11th July 2014 [Link]

Yin M, Guo Y and Gao J 2014 'Linear Subspace Learning via sparse dimension reduction', International Joint Conference on Neural Networks (IJCNN), Beijing, China, 11th July 2014 [Link]

Fu Y, Gao J, Tien D and Lin Z 2014 'Tensor LRR based subspace clustering', International Joint Conference on Neural Networks (IJCNN), Beijing, China, 11th July 2014 [Link]

Tierney S, Gao J and Guo Y 2014 'Subspace Clustering for Sequential Data', IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, United States, 28th June 2014 [Link]

Jiang X, Gao J, Hong X and Cai Z 2014 'Gaussian Processes Autoencoder for Dimensionality Reduction', Advances in Knowledge Discovery and Data Mining: Proceedings of Pacific-Asia Knowledge Discovery and Data Mining (PAKDD) Conference, Tainan, Taiwan, 16th May 2014 [Link]

Yin M, Gao J, Sun Y and Cai S 2014 'Blocky artifact removal with low-rank matrix recovery', IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, Italy, 9th May 2014 [Link]

2013

4
Journal Article/s

Chen D, Nguyen MN, Gao J and Shi D 2013 'On the construction of the relevance vector machine based on Bayesian Ying-Yang harmony learning', Neural Networks, vol.48, pp. 173–179 [Link]

Hong X, Gao J, Cheng S and Harris C 2013 'Particle swarm optimisation assisted classification using elastic net prefiltering', Neurocomputing, vol.122, pp. 210–220 [Link]

Shi D, Gao J, Rahmdel P, Antolovich M and Clark T 2013 'UND: Unite-and-Divide Method in Fourier and Radon Domains for Line Segment Detection', IEEE Transactions on Image Processing, vol.22:6, pp. 2500-2505 [Link]

6
Conference Proceeding/s

Guo Y, Gao J and Sun Y 2013 'Endmember Extraction by Exemplar Finder', Proceedings of Advanced Data Mining and Applications (ADMA) Conference, Hangzhou, China, 16th December 2013 [Link]

Tierney S, Gao J and Bull G 2013 'Image Matting for Sparse User Input by Iterative Refinement', Proceedings of Digital lmage Computing: Techniques and Applications (DlCTA) Conference, Hobart, Australia, 28th November 2013 [Link]

Li F, Tang L, Li C, Guo Y and Gao J 2013 'A new super resolution method based on combined sparse representations for remote sensing imagery', Proceedings of Society of Photo-Optical Instrumentation Engineers (SPIE) Conference, Dresden, Germany, 26th September 2013 [Link]

Gao J, Guo Y and Ying M 2013 'Restricted Boltzmann machine approach to couple dictionary training for image super-resolution', Proceedings of International Conference on Image Processing (ICIP), Melbourne, Australia, 18th September 2013 [Link]

Yin M and Gao J 2013 'Robust face recognition via double low-rank matrix recovery for feature extraction', Proceedings of International Conference on Image Processing (ICIP), Melbourne, Australia, 18th September 2013 [Link]

Guo Y, Gao J and Li F 2013 'Large scale hyperspectral data segmentation by random spatial subspace clustering', Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Melbourne, Australia, 26th July 2013 [Link]

Hong X, Guo Y, Chen S and Gao J 2013 'Sparse model construction using coordinate descent optimization', Proceedings of International Conference on Digital Signal Processing (DSP), Fira, Greece, 3rd July 2013 [Link]

Guo Y, Gao J and Li F 2013 'Dimensionality Reduction with Dimension Selection', Advances in Knowledge Discovery and Data Mining: Proceedings of Pacific-Asia Knowledge Discovery and Data Mining (PAKDD) Conference, Gold Coast, Australia, 17th April 2013 [Link]

2012

4
Journal Article/s

Gao J, Shi J and Caenano T 2012 'Dimensionality reduction via compressive sensing', Pattern Recognition Letters, vol.33:9, pp. 1163–1170 [Link]

Jiang X, Gao J, Wang T and Zheng L 2012 'Supervised Latent Linear Gaussian Process Latent Variable Model for Dimensionality Reduction', IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol.42:6, pp. 1620-1632 [Link]

6
Conference Proceeding/s

Guo Y, Gao J and Hong X 2012 'Constrained Grouped Sparsity', Proceedings of 25th anniversary of the Australasian Joint Conferences on Artificial Intelligence (AI 2012), Sydney, Australia, 7th December 2012 [Link]

Tierney S and Gao J 2012 'Natural Image Matting with Total Variation Regularisation', Proceedings of Digital lmage Computing: Techniques and Applications (DlCTA) Conference, Fremantle, Australia, 5th December 2012 [Link]

Bull G and Gao J 2012 'Transposed Low Rank Representation for Image Classification', Proceedings of Digital lmage Computing: Techniques and Applications (DlCTA) Conference, Fremantle, Australia, 5th December 2012 [Link]

Gao J, Liu J and Paul M 2012 'The Image Matting Method with Regularized Matte', Proceedings of IEEE International Conference on Multimedia and Expo (ICME), Melbourne, Australia, 13th July 2012 [Link]

Rahman MG, Islam MZ, Bossomaier T and Gao J 2012 'CAIRAD: A co-appearance based analysis for Incorrect Records and Attribute-values Detection', Proceedings of International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, 15th June 2012 [Link]

Letchford A, Gao J and Zheng L 2012 'Optimizing the moving average', Proceedings of International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, 15th June 2012 [Link]

Jiang X, Gao J, Shi D and Wang T 2012 'Thin Plate Spline Latent Variable Models for dimensionality reduction', Proceedings of International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, 15th June 2012 [Link]

Paul M, Gao J and Anotolovich M 2012 '3D motion estimation for 3D video coding', Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, 30th March 2012 [Link]

2011

2
Book Section/s

Abraham J, Kwan P and Gao J 2011 'Fingerprint Matching using A Hybrid Shape and Orientation Descriptor' in State of the art in Biometrics, ed. Yang J, Nanni L, InTech, United States, pp. 25-56 [Link]

4
Journal Article/s

Kwan P, Kameyama K, Gao J and Toraichi K 2011 'Content-based Image Retrieval of Cultural Heritage Symbols by Interaction of Visual Perspectives', International Journal of Pattern Recognition and Artificial Intelligence, vol.25:5, pp. 643-673 [Link]

6
Conference Proceeding/s

Bull G and Gao J 2011 'Classification of Hand-Written Digits Using Chordiograms', Proceedings of Digital lmage Computing: Techniques and Applications (DlCTA) Conference, Noosa Heads, Australia, 8th December 2011 [Link]

Gao J 2011 'Image Matting via Local Tangent Space Alignment', Proceedings of Digital lmage Computing: Techniques and Applications (DlCTA) Conference, Noosa Heads, Australia, 8th December 2011 [Link]

Gao J 2011 'Multi-task beta process sparse kernel machines', Proceedings of International Joint Conference on Neural Networks (IJCNN), San Jose, United States, 5th August 2011 [Link]

Guo Y and Gao J 2011 'Local Feature Based Tensor Kernel for Image Manifold Learning', Advances in Knowledge Discovery and Data Mining: Proceedings of Pacific-Asia Knowledge Discovery and Data Mining (PAKDD) Conference, Shenzhen, China, 27th May 2011 [Link]

Tong B, Gao J, Thach NH and Suzuki E 2011 'Gaussian Process for Dimensionality Reduction in Transfer Learning', Proceedings of the SIAM International Conference on Data Mining, Mesa, United States, 30th April 2011 [Link]

2010

4
Journal Article/s

Kwan P, Gao J, Guo Y and Kameyama K 2010 'A Learning Framework for Adaptive Fingerprint Identification', International Journal of Pattern Recognition and Artificial Intelligence, vol.24:1, pp. 15-38 [Link]

Gao J, Zhang J and Tian D 2010 'Relevance Units Latent Variable Model and Nonlinear Dimensionality Reduction', IEEE Transactions on Neural Networks and Learning Systems, vol.21:1, pp. 123-135 [Link]

Gao J, Kwan P and Shi D 2010 'Sparse kernel learning with LASSO and Bayesian inference algorithm', Neural Networks, vol.23:2, pp. 257–264 [Link]

6
Conference Proceeding/s

Lihong Zheng L, Gao J and He X 2010 'Efficient character segmentation on car license plates', Proceedings of International Conference on Control Automation Robotics & Vision (ICARCV), Singapore, Singapore, 10th December 2010 [Link]

Jiang X, Gao J, Wang T and Kwan PW 2010 'Learning Gradients with Gaussian Processes', Advances in Knowledge Discovery and Data Mining: Proceedings of Pacific-Asia Knowledge Discovery and Data Mining (PAKDD) Conference, Hyderabad, India, 24th June 2010 [Link]

2009

3
Edited Book/s

Gao J, Kwan PH, Poon J and Poon S 2009 'Proceedings of the workshop Advances and Issues in Biomedical Data Mining (AIBDM'09) in association with the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'09)', Printing House of Thammasat University - Rangsit Campus, Bangkok, Thailand

4
Journal Article/s

Gao J, Kwan P and Huang X 2009 'Comprehensive Analysis for the Local Fisher Discriminant Analysis', International Journal of Pattern Recognition and Artificial Intelligence, vol.23:6, pp. 1129-1143 [Link]

Gao J, Kwan P and Guo Y 2009 'Robust multivariate L1 principal component analysis and dimensionality reduction', Neurocomputing, vol.72:4-6, pp. 1242–1249 [Link]

2008

4
Journal Article/s

Gao J 2008 'Robust l1 principal component analysis and its bayesian variational inference', Neural Computation, vol.20:2, pp. 555-572 [Link]

Guo Y, Gao J and Kwan P 2008 'Twin Kernel Embedding', IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30:8, pp. 1490-1495 [Link]

6
Conference Proceeding/s

Gao J, Antolovich M and Kwan P 2008 'L1 LASSO Modeling and Its Bayesian Inference', Proceedings of Australasian Joint Conferences on Artificial Intelligence (AI 2008), Auckland, New Zealand, 5th December 2008 [Link]

Xu R, Gao J and Antolovich M 2008 'Novel methods for high-resolution facial image capture using calibrated PTZ and static cameras', Proceedings of IEEE International Conference on Multimedia and Expo (ICME), Hannover, Germany, 26th June 2008 [Link]

2007

3
Edited Book/s

Ong K-L, Li W and Gao J 2007 'The proceedings of the 2nd International Workshop on Integrating AI and Data Mining (AIDM 2007)', Australian Computer Society, Darlinghurst, Australia [Link]

4
Journal Article/s

Huang X, Lei W, Sajeev ASM and Gao J 2007 'A new algorithm for removing node overlapping in graph visualization', Information Sciences, vol.177:14, pp. 2821–2844 [Link]

Liu X, Kong B, Gao J and Zhang J 2007 'A sparse least squares support vector machine classifier', Pattern Recognition and Artificial Intelligence, vol.20:5, pp. 681-687 [Link]

Gao J, Shi DM and Liu XM 2007 'Significant vector learning to construct sparse kernel regression models', Neural Networks, vol.20:7, pp. 791-798 [Link]

Tian T, Xu S, Gao J and Burrage K 2007 'Simulated maximum likelihood method for estimating kinetic rates in gene expression', Bioinformatics, vol.23:1, pp. 84-91 [Link]

6
Conference Proceeding/s

Guo Y, Kwan PW and Gao J 2007 'Twin Kernel Embedding with Back Constraints', IEEE International Conference on Data Mining (ICDM), Omaha, United States, 31st October 2007 [Link]

Guo Y, Kwan PW and Gao J 2007 'Learning Optimal Kernel from Distance Metric in Twin Kernel Embedding for Dimensionality Reduction and Visualization of Fingerprints', Proceedings of Advanced Data Mining and Applications (ADMA) Conference, Harbin, China, 8th August 2007 [Link]

Liu X, Cao S, Gao J and Zhang J 2007 'The Kernelized Geometrical Bisection Methods', Proceedings of International Symposium on Neural Networks (ISNN), Nanjing, China, 7th June 2007 [Link]

2006

2
Book Section/s

Gao J and Zhang L 2006 'The Error Bar Estimation for the Soft Classification with Gaussian Process Models' in Applied Soft Computing Technologies: The Challenge of Complexity, ed. Abraham A, Baets B, Koeppen M, and Nickolay B, Springer, Berlin, Germany, pp. 675-683 [Link]

4
Journal Article/s

Shi D, Gao J and Ng GS 2006 'The construction of wavelet network for speech signal processing', Neural Computing & Applications, vol.15:3, pp. 217-222 [Link]

6
Conference Proceeding/s

Guo Y, Gao J and Kwan PW 2006 'Kernel Laplacian Eigenmaps for Visualization of Non-vectorial Data', Proceedings of Australasian Joint Conferences on Artificial Intelligence (AI 2006), Hobart, Australia, 8th December 2006 [Link]

Guo Y, Gao J and Kwan PW 2006 'Visualization of Non-vectorial Data Using Twin Kernel Embedding', Proceedings of International Workshop on Integrating AI and Data Mining (AIDM), Hobart, Australia, 5th December 2006 [Link]

Kwan PW, Gao J and Guo Y 2006 'Fingerprint Matching using Enhanced Shape Context', Proceedings of International Conference on Image and Vision Computing New Zealand (IVCNZ), Great Barrier Island, New Zealand, 29th November 2006

Guo Y and Gao J 2006 'Manifolds of Bag of Pixels: A Better Representation for Image Recognition', Proceedings of IEEE International Conference on Systems, Man and Cybernetics (SMC), Taipei, Taiwan, 11th October 2006 [Link]

Kwan PW and Gao J 2006 'A multi-step strategy for approximate similarity search in image databases', Proceedings of Australasian Database Conference (ADC), Hobart, Australia, 19th January 2006

2004

1
Book/s

Chau FT, Liang YZ, Gao J and Zhao S 2004 'Chemometrics: From Basics to Wavelet Transform', John Wiley & Sons, New Jersey, United States [Link]

Selected grants

Recent Units Taught

  • QBUS5001 Quantitative Methods for Business

    2017: S1,

  • QBUS6810 Statistical Learning and Data Mining

    2016: S2,

  • QBUS6840 Predictive Analytics

    2017: S1,
    2016: S1,

Newsroom articles

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