Papers published by Tongliang Liu. If you have questions regarding any of these publications, please feel free to contact me.

Preprints:




Learning with Bounded Instance-and Label-dependent Label Noise. [PDF]
Jiacheng Cheng, Tongliang Liu, Kotagiri Rao, and Dacheng Tao.



Learning with Biased Complementary Labels. [PDF]
Xiyu Yu, Tongliang Liu, Mingming Gong, and Dacheng Tao.



Transfer Learning with Label Noise. [PDF]
Xiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang, and Dacheng Tao.



Local Blur Mapping: Exploiting High-Level Semantics by Deep Neural Networks. [PDF]
Kede Ma, Huan Fu, Tongliang Liu, Zhou Wang, and Dacheng Tao.



Truncated Cauchy Non-negative Matrix Factorization.
Naiyang Guan*, Tongliang Liu*, Yangmuzi Zhang, Dacheng Tao, and Larry Steven Davis.
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), accepted.



Continuous Dropout.
Xu Shen, Xinmei Tian, Fang Xu, Tongliang Liu, and Dacheng Tao
IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), accepted.



Multi-class Learning with Partially Corrupted Labels.
Ruxin Wang, Tongliang Liu, and Dacheng Tao
IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), accepted.



On Better Exploring and Exploiting Task Relationship in Multi-Task Learning: Joint Model and Feature Learning.
Ya Li, Xinmei Tian, Tongliang Liu, and Dacheng Tao.
IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), accepted.



Supervised Discrete Hashing with Relaxation.
Jie Gui*, Tongliang Liu*, Zhenan Sun, Dacheng Tao, and Tieniu Tan.
IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), accepted.



A Regularization Approach for Instance-Based Superset Label Learning.
Chen Gong, Tongliang Liu, Yuanyan Tang, Jian Yang, Jie Yang, and Dacheng Tao.
IEEE Transactions on Cybernetics (T-CYB), accepted.

Journal papers:

2018



Fast Supervised Discrete Hashing. [PDF] [BibTeX]
Jie Gui*, Tongliang Liu*, Zhenan Sun, Dacheng Tao, and Tieniu Tan.
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 40(2): 490-496, 2018.

2017



Algorithm-Dependent Generalization Bounds for Multi-Task Learning. [PDF] [BibTeX]
Tongliang Liu, Dacheng Tao, Mingli Song, and Stephen J. Maybank.
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 39(2): 227-241, 2017.



Large Cone Non-negative Matrix Factorization. [PDF] [BibTeX] [MATLAB CODE]
Tongliang Liu, Mingming Gong, and Dacheng Tao.
IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 28(9): 2129-2141, 2017.



dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs. [PDF] [BibTeX] [MATLAB CODE]
Kede Ma, Wentao Liu, Tongliang Liu, Zhou Wang, and Dacheng Tao.
IEEE Transactions on Image Processing (T-IP), 26(8): 3951-3964, 2017.



Elastic Net Hypergraph Learning for Image Clustering and Semi-supervised Classification. [PDF] [BibTeX]
Qingshan Liu, Yubao Sun, Cantian Wang, Tongliang Liu, Dacheng Tao.
IEEE Transactions on Image Processing (T-IP), 26(1): 452-463, 2017.



Spectral Ensemble Clustering via Weighted K-means: Theoretical and Practical Evidence.
Hongfu Liu, Junjie Wu, Tongliang Liu, Dacheng Tao, and Yun Fu.
IEEE Transactions on Knowledge and Data Engineering (T-KDE), vol. 29, no. 5, pp. 1129-1143, 2017.



Joint Sparse Representation and Multitask Learning for Hyperspectral Target Detection. [BibTeX]
Yuxiang Zhang, Bo Du, Liangpei Zhang, and Tongliang Liu.
IEEE Transactions on Geoscience and Remote Sensing (T-GRS), 55(2): 894-906, 2017.

2016



Classification with Noisy Labels by Importance Reweighting. [PDF] [BibTeX] [MATLAB CODE]
Tongliang Liu and Dacheng Tao.
IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 38(3): 447-461, 2016.



Dimensionality-Dependent Generalization Bounds for k-Dimensional Coding Schemes. [PDF] [BibTeX]
Tongliang Liu, Dacheng Tao, and Dong Xu.
Neural Computation (NECO), 28(10): 2213-2249, 2016.



On the Performance of MahNMF Manhattan Non-negative Matrix Factorization. [PDF] [BibTeX]
Tongliang Liu and Dacheng Tao.
IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 27(9): 1851-1863, 2016.



Local Rademacher Complexity for Multi-Label Learning. [PDF] [BibTeX]
Chang Xu, Tongliang Liu, Dacheng Tao, and Chao Xu.
IEEE Transactions on Image Processing (T-IP), 25(3): 1495-1507, 2016.



Dual Diversified Dynamical Gaussian Process Latent Variable Model for Video Repair. [PDF] [BibTeX]
Hao Xiong, Tongliang Liu, Dacheng Tao, and Heng Tao Shen.
IEEE Transactions on Image Processing (T-IP), 25(8): 3626-3637, 2016.



Representative Vector Machines: A Unified Framework for Classical Classifiers. [PDF] [BibTeX]
Jie Gui*, Tongliang Liu*, Dacheng Tao, Zhenan Sun, and Tieniu Tan.
IEEE Transactions on Cybernetics (T-CYB), 46(8): 1877-1888, 2016.



Video Face Editing Using Temporal-Spatial-Smooth Warping. [PDF] [BibTeX]
Xiaoyan Li, Tongliang Liu, Jiankang Deng, and Dacheng Tao.
ACM Transactions on Intelligent Systems and Technology (ACM-TIST), 7(3): 32, 2016.

2015



Deformed Graph Laplacian for Semisupervised Learning. [PDF] [BibTeX]
Chen Gong, Tongliang Liu and Dacheng Tao, Keren Fu, Enmei Tu, and Jie Yang.
IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 26(10): 2261-2274, 2015.



Multiview Matrix Completion for Multilabel Image Classification. [PDF] [BibTeX]
Yong Luo, Tongliang Liu, Dacheng Tao, and Chao Xu.
IEEE Transactions on Image Processing (T-IP), 24(8): 2261-2274, 2015.



No Reference Quality Assessment for Multiply-Distorted Images Based on an Improved Bag-of-Words Model. [PDF] [BibTeX]
Yanan Lu, Fengying Xie, Tongliang Liu, Zhiguo Jiang, and Dacheng Tao.
IEEE Signal Processing Letters (IEEE-SPL), 22(10): 1811-1815, 2015.

2014



Decomposition-Based Transfer Distance Metric Learning for Image Classification. [PDF] [BibTeX]
Yong Luo, Tongliang Liu, Dacheng Tao, and Chao Xu.
IEEE Transactions on Image Processing (T-IP), 23(9): 3789-3801, 2014.

Conference papers:



Domain Generalization via Conditional Invariant Representations.
Ya Li, Mingming Gong, Xinmei Tian, Tongliang Liu, and Dacheng Tao.
The 32th AAAI Conference on Artificial Intelligence (AAAI 2018): Accepted.



General Heterogeneous Transfer Distance Metric Learning via Knowledge Fragments Transfer. [PDF] [BibTeX]
Yong Luo, Yonggang Wen, Tongliang Liu, and Dacheng Tao. [Distinguished Paper Candidate]
The 2017 International Joint Conference on Artificial Intelligence (IJCAI 2017): 2450-2456



Understanding How Feature Structure Transfers in Transfer Learning. [PDF] [BibTeX]
Tongliang Liu, Qiang Yang, and Dacheng Tao.
The 2017 International Joint Conference on Artificial Intelligence (IJCAI 2017): 2365-2371.



Algorithmic Stability and Hypothesis Complexity. [PDF] [BibTeX]
Tongliang Liu, Gábor Lugosi, Gergely Neu, and Dacheng Tao.
The 34th International Conference on Machine Learning (ICML 2017): 2159-2167.



On Compressing Deep Models by Low Rank and Sparse Decomposition. [PDF] [BibTeX]
Xiyu Yu, Tongliang Liu, Xinchao Wang, and Dacheng Tao.
The 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017): 7370-7379.



Domain Adaptation with Conditional Transferable Components. [PDF] [BibTeX]
Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, and Bernhard Schölkopf.
The 33rd International Conference on Machine Learning (ICML 2016): 2839-2848.



Diversified Dynamical Gaussian Process Latent Variable Model for Video Repair. [PDF] [BibTeX]
Hao Xiong, Tongliang Liu, and Dacheng Tao.
The 30th AAAI Conference on Artificial Intelligence (AAAI 2016): 3641-3647.



Spectral Ensemble Clustering. [PDF] [BibTeX]
Hongfu Liu*, Tongliang Liu*, Junjie Wu, Dacheng Tao, and Yun Fu. [*: equally contributed]
The 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2015): 715-724.



Multi-Task Model and Feature Joint Learning. [PDF] [BibTeX]
Ya Li, Xinmei Tian, Tongliang Liu, and Dacheng Tao.
The 2015 International Joint Conference on Artificial Intelligence (IJCAI 2015): 3643-3649.



On the Robustness and Generalization of Cauchy Regression. [PDF] [BibTeX] [Best Paper Award]
Tongliang Liu and Dacheng Tao.
The 2014 IEEE International Conference on Information Science and Technology (ICIST 2014): 100-105.



Learning Relative Features through Adaptive Pooling for Image Classification. [PDF] [BibTeX] [Best Paper Award candidate]
Ming Shao, Sheng Li, Tongliang Liu, Dacheng Tao, Thomas S. Huang, and Yun Fu.
The 2014 IEEE International Conference on Multimedia and Expo (ICME 2014): 1-6.