Dr Tongliang Liu

BEng (USTC) PhD (UTS)
Lecturer
Statistical Learning Theory and Machine Learning
School of Information Technologies

J12 - The School of Information Technologies
The University of Sydney

Telephone +61 2 8627 5966

Website School of Information Technologies

Personal site

Biographical details

Tongliang Liu is a Lecturer in machine learning at the School of Information Technologies, The University of Sydney. He received the BEng degree in electronic engineering and information science from the University of Science and Technology of China, and the PhD degree from the University of Technology Sydney. From October 2015 to March 2016, he was a visiting PhD student with Barcelona Graduate School of Economics (Barcelona GSE) and the Department of Economics at Pompeu Fabra University, Spain. Prior to joining The University of Sydney, he was a Lecturer at the University of Technology Sydney.

His research interests lie in providing mathematical and theoretical foundations to justify and further understand machine learning models and designing efficient learning algorithms for problems in computer vision and data mining, with a particular emphasis on matrix factorisation, transfer learning, multi-task learning, and learning with label noise.

Awards and honours

  • Distinguished Paper Candidate - International Joint Conference on Artificial Intelligence (IJCAI) 2017
  • IEEE Transactions on Cybernetics Outstanding Reviewer - IEEE 2016
  • Best Paper Candidate - IEEE International Conference on Multimedia & Expo (ICME) 2014
  • Best Paper Award - IEEE International Conference on Information Science & Tech (ICIST) 2014
  • Computational Statistics & Data Analysis Outstanding Reviewer - ELSEVIER 2014

Selected publications

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Journals

  • Liu, T., Tao, D., Song, M., Maybank, S. (2017). Algorithm-Dependent Generalization Bounds for Multi-Task Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(2), 227-241. [More Information]
  • Liu, Q., Sun, Y., Wang, C., Liu, T., Tao, D. (2017). Elastic net hypergraph learning for image clustering and semi-supervised classification. IEEE Transactions on Image Processing, 26(1), 452-463. [More Information]
  • Zhang, Y., Du, B., Zhang, L., Liu, T. (2017). Joint Sparse Representation and Multitask Learning for Hyperspectral Target Detection. IEEE Transactions on Geoscience and Remote Sensing, 55(2), 894-906. [More Information]
  • Liu, H., Wu, J., Liu, T., Tao, D., Fu, Y. (2017). Spectral Ensemble Clustering via Weighted K-means: Theoretical and Practical Evidence. IEEE Transactions On Knowledge And Data Engineering, 29(5), 1129-1143. [More Information]
  • Gui, J., Liu, T., Sun, Z., Tao, D., Tan, T. (2017). Supervised Discrete Hashing with Relaxation (Forthcoming). IEEE Transactions on Neural Networks and Learning Systems, 23. [More Information]
  • Liu, T., Gong, M., Tao, D. (2016). A Large-Cone Nonnegative Matrix Factorization. IEEE Transactions on Neural Networks and Learning Systems, 23.
  • Liu, T., Tao, D. (2016). Classification with Noisy Labels by Importance Reweighting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(3), 447-461. [More Information]
  • Liu, T., Tao, D., Xu, D. (2016). Dimensionality-Dependent Generalization Bounds for k-Dimensional Coding Schemes. Neural Computation, 28(10), 2213-2249. [More Information]
  • Xiong, H., Liu, T., Tao, D., Shen, H. (2016). Dual Diversified Dynamical Gaussian Process Latent Variable Model for Video Repairing. IEEE Transactions on Image Processing, 25(8), 3626-3637. [More Information]
  • Xu, C., Liu, T., Tao, D., Xu, C. (2016). Local Rademacher Complexity for Multi-Label Learning. IEEE Transactions on Image Processing, 25(3), 1495-1507. [More Information]
  • Liu, T., Tao, D. (2016). On the performance of Manhattan nonnegative matrix factorization. IEEE Transactions on Neural Networks and Learning Systems, 27(9), 1851-1863. [More Information]
  • Gui, J., Liu, T., Tao, D., Sun, Z., Tan, T. (2016). Representative Vector Machines: A Unified Framework for Classical Classifiers. IEEE Transactions on Cybernetics, 46(8), 1877-1888. [More Information]
  • Li, X., Liu, T., Deng, J., Tao, D. (2016). Video face editing using temporal-spatial-smooth warping. ACM Transactions on Intelligent Systems and Technology, 7(3), 1-28. [More Information]
  • Gong, C., Liu, T., Tao, D., Fu, K., Tu, E., Yang, J. (2015). Deformed Graph Laplacian for Semisupervised Learning. IEEE Transactions on Neural Networks and Learning Systems, 26(10), 2261-2274. [More Information]
  • Luo, Y., Liu, T., Tao, D., Xu, C. (2015). Multiview matrix completion for multilabel image classification. IEEE Transactions on Image Processing, 24(8), 2355-2368. [More Information]
  • Lu, Y., Xie, F., Liu, T., Jiang, Z., Tao, D. (2015). No Reference Quality Assessment for Multiply-Distorted Images Based on an Improved Bag-of-Words Model. IEEE Signal Processing Letters, 22(10), 1811-1815. [More Information]
  • Luo, Y., Liu, T., Tao, D., Xu, C. (2014). Decomposition-based transfer distance metric learning for image classification. IEEE Transactions on Image Processing, 23(9), 3789-3801. [More Information]

Conferences

  • Xiong, H., Liu, T., Tao, D. (2016). Diversified Dynamical Gaussian Process Latent Variable Model for Video Repair. 30th AAAI Conference on Artificial Intelligence (AAAI 2016), United States: AAAI Press.
  • Gong, M., Zhang, K., Liu, T., Tao, D., Glymour, C., Scholkopf, B. (2016). Domain Adaptation with Conditional Transferable Components. 33rd International Conference on Machine Learning (ICML 2016), New York: Journal of Machine Learning Research (JMLR).
  • Li, Y., Tian, X., Liu, T., Tao, D. (2015). Multi-task model and feature joint learning. 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), Buenos Aires: AAAI Press.
  • Liu, H., Liu, T., Wu, J., Tao, D., Fu, Y. (2015). Spectral ensemble clustering. The 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2015), New York: Association for Computing Machinery (ACM). [More Information]
  • Shao, M., Li, S., Liu, T., Tao, D., Huang, T., Fu, Y. (2014). Learning relative features through adaptive pooling for image classification. 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW 2014), Piscataway, New Jersey: IEEE. [More Information]
  • Liu, T., Tao, D. (2014). On the robustness and generalization of Cauchy regression. 2014 4th IEEE International Conference on Information Science and Technology (ICIST 2014), Piscataway: IEEE. [More Information]

2017

  • Liu, T., Tao, D., Song, M., Maybank, S. (2017). Algorithm-Dependent Generalization Bounds for Multi-Task Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(2), 227-241. [More Information]
  • Liu, Q., Sun, Y., Wang, C., Liu, T., Tao, D. (2017). Elastic net hypergraph learning for image clustering and semi-supervised classification. IEEE Transactions on Image Processing, 26(1), 452-463. [More Information]
  • Zhang, Y., Du, B., Zhang, L., Liu, T. (2017). Joint Sparse Representation and Multitask Learning for Hyperspectral Target Detection. IEEE Transactions on Geoscience and Remote Sensing, 55(2), 894-906. [More Information]
  • Liu, H., Wu, J., Liu, T., Tao, D., Fu, Y. (2017). Spectral Ensemble Clustering via Weighted K-means: Theoretical and Practical Evidence. IEEE Transactions On Knowledge And Data Engineering, 29(5), 1129-1143. [More Information]
  • Gui, J., Liu, T., Sun, Z., Tao, D., Tan, T. (2017). Supervised Discrete Hashing with Relaxation (Forthcoming). IEEE Transactions on Neural Networks and Learning Systems, 23. [More Information]

2016

  • Liu, T., Gong, M., Tao, D. (2016). A Large-Cone Nonnegative Matrix Factorization. IEEE Transactions on Neural Networks and Learning Systems, 23.
  • Liu, T., Tao, D. (2016). Classification with Noisy Labels by Importance Reweighting. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(3), 447-461. [More Information]
  • Liu, T., Tao, D., Xu, D. (2016). Dimensionality-Dependent Generalization Bounds for k-Dimensional Coding Schemes. Neural Computation, 28(10), 2213-2249. [More Information]
  • Xiong, H., Liu, T., Tao, D. (2016). Diversified Dynamical Gaussian Process Latent Variable Model for Video Repair. 30th AAAI Conference on Artificial Intelligence (AAAI 2016), United States: AAAI Press.
  • Gong, M., Zhang, K., Liu, T., Tao, D., Glymour, C., Scholkopf, B. (2016). Domain Adaptation with Conditional Transferable Components. 33rd International Conference on Machine Learning (ICML 2016), New York: Journal of Machine Learning Research (JMLR).
  • Xiong, H., Liu, T., Tao, D., Shen, H. (2016). Dual Diversified Dynamical Gaussian Process Latent Variable Model for Video Repairing. IEEE Transactions on Image Processing, 25(8), 3626-3637. [More Information]
  • Xu, C., Liu, T., Tao, D., Xu, C. (2016). Local Rademacher Complexity for Multi-Label Learning. IEEE Transactions on Image Processing, 25(3), 1495-1507. [More Information]
  • Liu, T., Tao, D. (2016). On the performance of Manhattan nonnegative matrix factorization. IEEE Transactions on Neural Networks and Learning Systems, 27(9), 1851-1863. [More Information]
  • Gui, J., Liu, T., Tao, D., Sun, Z., Tan, T. (2016). Representative Vector Machines: A Unified Framework for Classical Classifiers. IEEE Transactions on Cybernetics, 46(8), 1877-1888. [More Information]
  • Li, X., Liu, T., Deng, J., Tao, D. (2016). Video face editing using temporal-spatial-smooth warping. ACM Transactions on Intelligent Systems and Technology, 7(3), 1-28. [More Information]

2015

  • Gong, C., Liu, T., Tao, D., Fu, K., Tu, E., Yang, J. (2015). Deformed Graph Laplacian for Semisupervised Learning. IEEE Transactions on Neural Networks and Learning Systems, 26(10), 2261-2274. [More Information]
  • Li, Y., Tian, X., Liu, T., Tao, D. (2015). Multi-task model and feature joint learning. 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), Buenos Aires: AAAI Press.
  • Luo, Y., Liu, T., Tao, D., Xu, C. (2015). Multiview matrix completion for multilabel image classification. IEEE Transactions on Image Processing, 24(8), 2355-2368. [More Information]
  • Lu, Y., Xie, F., Liu, T., Jiang, Z., Tao, D. (2015). No Reference Quality Assessment for Multiply-Distorted Images Based on an Improved Bag-of-Words Model. IEEE Signal Processing Letters, 22(10), 1811-1815. [More Information]
  • Liu, H., Liu, T., Wu, J., Tao, D., Fu, Y. (2015). Spectral ensemble clustering. The 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2015), New York: Association for Computing Machinery (ACM). [More Information]

2014

  • Luo, Y., Liu, T., Tao, D., Xu, C. (2014). Decomposition-based transfer distance metric learning for image classification. IEEE Transactions on Image Processing, 23(9), 3789-3801. [More Information]
  • Shao, M., Li, S., Liu, T., Tao, D., Huang, T., Fu, Y. (2014). Learning relative features through adaptive pooling for image classification. 2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW 2014), Piscataway, New Jersey: IEEE. [More Information]
  • Liu, T., Tao, D. (2014). On the robustness and generalization of Cauchy regression. 2014 4th IEEE International Conference on Information Science and Technology (ICIST 2014), Piscataway: IEEE. [More Information]

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