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2020 – today
- 2020
[j37]Xinwang Liu
, Xinzhong Zhu, Miaomiao Li, Lei Wang, En Zhu, Tongliang Liu, Marius Kloft, Dinggang Shen, Jianping Yin, Wen Gao:
Multiple Kernel $k$k-Means with Incomplete Kernels. IEEE Trans. Pattern Anal. Mach. Intell. 42(5): 1191-1204 (2020)- [j36]Xinwang Liu, Lei Wang, Xinzhong Zhu, Miaomiao Li, En Zhu, Tongliang Liu, Li Liu, Yong Dou, Jianping Yin:
Absent Multiple Kernel Learning Algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 42(6): 1303-1316 (2020) - [j35]Erkun Yang, Tongliang Liu, Cheng Deng, Dacheng Tao:
Adversarial Examples for Hamming Space Search. IEEE Trans. Cybern. 50(4): 1473-1484 (2020) - [j34]Xinpeng Ding, Nannan Wang, Xinbo Gao, Jie Li, Xiaoyu Wang, Tongliang Liu:
Group Feedback Capsule Network. IEEE Trans. Image Process. 29: 6789-6799 (2020) - [j33]Cheng Deng, Erkun Yang, Tongliang Liu, Dacheng Tao:
Two-Stream Deep Hashing With Class-Specific Centers for Supervised Image Search. IEEE Trans. Neural Networks Learn. Syst. 31(6): 2189-2201 (2020) - [j32]Yang Wei, Chen Gong, Shuo Chen, Tongliang Liu, Jian Yang, Dacheng Tao:
Harnessing Side Information for Classification Under Label Noise. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3178-3192 (2020) - [c28]Maoying Qiao, Jun Yu, Tongliang Liu, Xinchao Wang, Dacheng Tao:
Diversified Bayesian Nonnegative Matrix Factorization. AAAI 2020: 5420-5427 - [c27]Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich:
Generative-Discriminative Complementary Learning. AAAI 2020: 6526-6533 - [c26]Shikang Gan, Yong Luo, Yonggang Wen, Tongliang Liu, Han Hu:
Deep Heterogeneous Multi-Task Metric Learning for Visual Recognition and Retrieval. ACM Multimedia 2020: 1837-1845 - [i48]Antonin Berthon, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama:
Confidence Scores Make Instance-dependent Label-noise Learning Possible. CoRR abs/2001.03772 (2020) - [i47]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao:
Towards Mixture Proportion Estimation without Irreducibility. CoRR abs/2002.03673 (2020) - [i46]Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu:
Multi-Class Classification from Noisy-Similarity-Labeled Data. CoRR abs/2002.06508 (2020) - [i45]Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao, Nana Liu:
Quantum noise protects quantum classifiers against adversaries. CoRR abs/2003.09416 (2020) - [i44]Maoying Qiao, Tongliang Liu, Jun Yu, Wei Bian, Dacheng Tao:
Repulsive Mixture Models of Exponential Family PCA for Clustering. CoRR abs/2004.03112 (2020) - [i43]Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama:
Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning. CoRR abs/2006.07805 (2020) - [i42]Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu:
Class2Simi: A New Perspective on Learning with Label Noise. CoRR abs/2006.07831 (2020) - [i41]Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama:
Parts-dependent Label Noise: Towards Instance-dependent Label Noise. CoRR abs/2006.07836 (2020) - [i40]Xinpeng Ding, Nannan Wang, Xinbo Gao, Jie Li, Xiaoyu Wang, Tongliang Liu:
Weakly Supervised Temporal Action Localization with Segment-Level Labels. CoRR abs/2007.01598 (2020) - [i39]Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Shan You, Dacheng Tao:
Quantum differentially private sparse regression learning. CoRR abs/2007.11921 (2020) - [i38]Heliang Huang, Yuxuan Du, Ming Gong, Youwei Zhao, Yulin Wu, Chaoyue Wang, Shaowei Li, Futian Liang, Jin Lin, Yu Xu, Rui Yang, Tongliang Liu, Min-Hsiu Hsieh, Hui Deng, Hao Rong, Cheng-Zhi Peng, Chao-Yang Lu, Yu-Ao Chen, Dacheng Tao, Xiaobo Zhu, Jian-Wei Pan:
Experimental Quantum Generative Adversarial Networks for Image Generation. CoRR abs/2010.06201 (2020) - [i37]Ruize Gao, Feng Liu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Masashi Sugiyama:
Maximum Mean Discrepancy is Aware of Adversarial Attacks. CoRR abs/2010.11415 (2020)
2010 – 2019
- 2019
- [j31]C. L. Philip Chen, Xinge You, Xinbo Gao, Tongliang Liu, Fionn Murtagh, Weifeng Liu:
Advances in data representation and learning for pattern analysis. Neurocomputing 348: 1-2 (2019) - [j30]Naiyang Guan, Tongliang Liu, Yangmuzi Zhang, Dacheng Tao, Larry S. Davis:
Truncated Cauchy Non-Negative Matrix Factorization. IEEE Trans. Pattern Anal. Mach. Intell. 41(1): 246-259 (2019) - [j29]Yong Luo, Yonggang Wen, Tongliang Liu, Dacheng Tao:
Transferring Knowledge Fragments for Learning Distance Metric from a Heterogeneous Domain. IEEE Trans. Pattern Anal. Mach. Intell. 41(4): 1013-1026 (2019) - [j28]Cheng Deng, Erkun Yang, Tongliang Liu, Jie Li, Wei Liu, Dacheng Tao:
Unsupervised Semantic-Preserving Adversarial Hashing for Image Search. IEEE Trans. Image Process. 28(8): 4032-4044 (2019) - [j27]Tao Lei, Xiaohong Jia, Tongliang Liu, Shigang Liu, Hongying Meng, Asoke K. Nandi:
Adaptive Morphological Reconstruction for Seeded Image Segmentation. IEEE Trans. Image Process. 28(11): 5510-5523 (2019) - [j26]Xinmei Tian, Ya Li, Tongliang Liu, Xinchao Wang, Dacheng Tao:
Eigenfunction-Based Multitask Learning in a Reproducing Kernel Hilbert Space. IEEE Trans. Neural Networks Learn. Syst. 30(6): 1818-1830 (2019) - [j25]Chen Gong, Tongliang Liu, Jian Yang, Dacheng Tao:
Large-Margin Label-Calibrated Support Vector Machines for Positive and Unlabeled Learning. IEEE Trans. Neural Networks Learn. Syst. 30(11): 3471-3483 (2019) - [c25]Erkun Yang, Tongliang Liu, Cheng Deng, Wei Liu, Dacheng Tao:
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs. CVPR 2019: 2946-2955 - [c24]Yihang Lou, Ling-Yu Duan, Yong Luo, Ziqian Chen, Tongliang Liu, Shiqi Wang, Wen Gao:
Towards Digital Retina in Smart Cities: A Model Generation, Utilization and Communication Paradigm. ICME 2019: 19-24 - [c23]Chuang Zhang, Dexin Ren, Tongliang Liu, Jian Yang, Chen Gong:
Positive and Unlabeled Learning with Label Disambiguation. IJCAI 2019: 4250-4256 - [c22]Yasutaka Furusho, Tongliang Liu, Kazushi Ikeda:
Skipping Two Layers in ResNet Makes the Generalization Gap Smaller than Skipping One or No Layer. INNSBDDL 2019: 349-358 - [c21]Fengxiang He, Tongliang Liu, Dacheng Tao:
Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence. NeurIPS 2019: 1141-1150 - [c20]Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama:
Are Anchor Points Really Indispensable in Label-Noise Learning? NeurIPS 2019: 6835-6846 - [i36]Yanwu Xu, Mingming Gong, Tongliang Liu, Kayhan Batmanghelich, Chaohui Wang:
Robust Angular Local Descriptor Learning. CoRR abs/1901.07076 (2019) - [i35]Fengxiang He, Tongliang Liu, Dacheng Tao:
Why ResNet Works? Residuals Generalize. CoRR abs/1904.01367 (2019) - [i34]Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich:
Generative-Discriminative Complementary Learning. CoRR abs/1904.01612 (2019) - [i33]Ya Li, Xinmei Tian, Tongliang Liu, Dacheng Tao:
On Better Exploring and Exploiting Task Relationships in Multi-Task Learning: Joint Model and Feature Learning. CoRR abs/1904.01747 (2019) - [i32]Chen Gong, Tongliang Liu, Yuanyan Tang, Jian Yang, Jie Yang, Dacheng Tao:
A Regularization Approach for Instance-Based Superset Label Learning. CoRR abs/1904.02832 (2019) - [i31]Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan:
Supervised Discrete Hashing with Relaxation. CoRR abs/1904.03549 (2019) - [i30]Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan:
Fast Supervised Discrete Hashing. CoRR abs/1904.03556 (2019) - [i29]Yong Luo, Tongliang Liu, Dacheng Tao, Chao Xu:
Decomposition-Based Transfer Distance Metric Learning for Image Classification. CoRR abs/1904.03846 (2019) - [i28]Yong Luo, Tongliang Liu, Dacheng Tao, Chao Xu:
Multi-View Matrix Completion for Multi-Label Image Classification. CoRR abs/1904.03901 (2019) - [i27]Tao Lei, Xiaohong Jia, Tongliang Liu, Shigang Liu, Hongying Meng, Asoke K. Nandi:
Adaptive Morphological Reconstruction for Seeded Image Segmentation. CoRR abs/1904.03973 (2019) - [i26]Yong Luo, Yonggang Wen, Tongliang Liu, Dacheng Tao:
Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain. CoRR abs/1904.04061 (2019) - [i25]Kede Ma, Wentao Liu, Tongliang Liu, Zhou Wang, Dacheng Tao:
dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs. CoRR abs/1904.06505 (2019) - [i24]Erkun Yang, Tongliang Liu, Cheng Deng, Wei Liu, Dacheng Tao:
DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs. CoRR abs/1905.03465 (2019) - [i23]Kui Jia, Shuai Li, Yuxin Wen, Tongliang Liu, Dacheng Tao:
Orthogonal Deep Neural Networks. CoRR abs/1905.05929 (2019) - [i22]Xiaobo Xia, Tongliang Liu, Nannan Wang, Bo Han, Chen Gong, Gang Niu, Masashi Sugiyama:
Are Anchor Points Really Indispensable in Label-Noise Learning? CoRR abs/1906.00189 (2019) - [i21]Naiyang Guan, Tongliang Liu, Yangmuzi Zhang, Dacheng Tao, Larry S. Davis:
Truncated Cauchy Non-negative Matrix Factorization. CoRR abs/1906.00495 (2019) - [i20]Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao:
A Quantum-inspired Algorithm for General Minimum Conical Hull Problems. CoRR abs/1907.06814 (2019) - [i19]Yihang Lou, Ling-Yu Duan, Yong Luo, Ziqian Chen, Tongliang Liu, Shiqi Wang, Wen Gao:
Towards Digital Retina in Smart Cities: A Model Generation, Utilization and Communication Paradigm. CoRR abs/1907.13368 (2019) - [i18]Jingfeng Zhang, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama:
Where is the Bottleneck of Adversarial Learning with Unlabeled Data? CoRR abs/1911.08696 (2019) - [i17]Xu Shen, Xinmei Tian, Tongliang Liu, Fang Xu, Dacheng Tao:
Continuous Dropout. CoRR abs/1911.12675 (2019) - [i16]Zhe Chen, Wanli Ouyang, Tongliang Liu, Dacheng Tao:
A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection. CoRR abs/1912.07010 (2019) - 2018
- [j24]Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan:
Fast Supervised Discrete Hashing. IEEE Trans. Pattern Anal. Mach. Intell. 40(2): 490-496 (2018) - [j23]Chen Gong, Tongliang Liu, Yuanyan Tang, Jian Yang, Jie Yang, Dacheng Tao:
A Regularization Approach for Instance-Based Superset Label Learning. IEEE Trans. Cybern. 48(3): 967-978 (2018) - [j22]Kede Ma, Huan Fu, Tongliang Liu, Zhou Wang, Dacheng Tao:
Deep Blur Mapping: Exploiting High-Level Semantics by Deep Neural Networks. IEEE Trans. Image Process. 27(10): 5155-5166 (2018) - [j21]Jie Gui, Tongliang Liu, Zhenan Sun, Dacheng Tao, Tieniu Tan:
Supervised Discrete Hashing With Relaxation. IEEE Trans. Neural Networks Learn. Syst. 29(3): 608-617 (2018) - [j20]Ya Li, Xinmei Tian, Tongliang Liu, Dacheng Tao:
On Better Exploring and Exploiting Task Relationships in Multitask Learning: Joint Model and Feature Learning. IEEE Trans. Neural Networks Learn. Syst. 29(5): 1975-1985 (2018) - [j19]Ruxin Wang, Tongliang Liu, Dacheng Tao:
Multiclass Learning With Partially Corrupted Labels. IEEE Trans. Neural Networks Learn. Syst. 29(6): 2568-2580 (2018) - [j18]Xu Shen, Xinmei Tian, Tongliang Liu, Fang Xu, Dacheng Tao:
Continuous Dropout. IEEE Trans. Neural Networks Learn. Syst. 29(9): 3926-3937 (2018) - [c19]Ya Li, Mingming Gong, Xinmei Tian, Tongliang Liu, Dacheng Tao:
Domain Generalization via Conditional Invariant Representations. AAAI 2018: 3579-3587 - [c18]Hong Tao, Chenping Hou, Xinwang Liu, Tongliang Liu, Dongyun Yi, Jubo Zhu:
Reliable Multi-View Clustering. AAAI 2018: 4123-4130 - [c17]Yanwu Xu, Mingming Gong, Tongliang Liu, Kayhan Batmanghelich, Chaohui Wang:
Robust Angular Local Descriptor Learning. ACCV (5) 2018: 420-435 - [c16]Xiyu Yu, Tongliang Liu, Mingming Gong, Kayhan Batmanghelich, Dacheng Tao:
An Efficient and Provable Approach for Mixture Proportion Estimation Using Linear Independence Assumption. CVPR 2018: 4480-4489 - [c15]Xiyu Yu, Tongliang Liu, Mingming Gong, Dacheng Tao:
Learning with Biased Complementary Labels. ECCV (1) 2018: 69-85 - [c14]Baosheng Yu, Tongliang Liu, Mingming Gong, Changxing Ding, Dacheng Tao:
Correcting the Triplet Selection Bias for Triplet Loss. ECCV (6) 2018: 71-86 - [c13]Ya Li, Xinmei Tian, Mingming Gong, Yajing Liu, Tongliang Liu, Kun Zhang, Dacheng Tao:
Deep Domain Generalization via Conditional Invariant Adversarial Networks. ECCV (15) 2018: 647-663 - [c12]Erkun Yang, Cheng Deng, Tongliang Liu, Wei Liu, Dacheng Tao:
Semantic Structure-based Unsupervised Deep Hashing. IJCAI 2018: 1064-1070 - [c11]Yuxuan Du, Tongliang Liu, Yinan Li, Runyao Duan, Dacheng Tao:
Quantum Divide-and-Conquer Anchoring for Separable Non-negative Matrix Factorization. IJCAI 2018: 2093-2099 - [c10]Yong Luo, Tongliang Liu, Yonggang Wen, Dacheng Tao:
Online Heterogeneous Transfer Metric Learning. IJCAI 2018: 2525-2531 - [i15]Jingwei Zhang, Tongliang Liu, Dacheng Tao:
On the Rates of Convergence from Surrogate Risk Minimizers to the Bayes Optimal Classifier. CoRR abs/1802.03688 (2018) - [i14]Jingwei Zhang, Tongliang Liu, Dacheng Tao:
An Information-Theoretic View for Deep Learning. CoRR abs/1804.09060 (2018) - [i13]Ya Li, Mingming Gong, Xinmei Tian, Tongliang Liu, Dacheng Tao:
Domain Generalization via Conditional Invariant Representation. CoRR abs/1807.08479 (2018) - [i12]Fengxiang He, Tongliang Liu, Geoffrey I. Webb, Dacheng Tao:
Instance-Dependent PU Learning by Bayesian Optimal Relabeling. CoRR abs/1808.02180 (2018) - [i11]Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao:
Implementable Quantum Classifier for Nonlinear Data. CoRR abs/1809.06056 (2018) - [i10]Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Dacheng Tao:
The Expressive Power of Parameterized Quantum Circuits. CoRR abs/1810.11922 (2018) - [i9]Jingwei Zhang, Tongliang Liu, Dacheng Tao:
An Optimal Transport View on Generalization. CoRR abs/1811.03270 (2018) - 2017
- [j17]Tongliang Liu, Dacheng Tao, Mingli Song, Stephen J. Maybank:
Algorithm-Dependent Generalization Bounds for Multi-Task Learning. IEEE Trans. Pattern Anal. Mach. Intell. 39(2): 227-241 (2017) - [j16]Yuxiang Zhang, Bo Du, Liangpei Zhang, Tongliang Liu:
Joint Sparse Representation and Multitask Learning for Hyperspectral Target Detection. IEEE Trans. Geosci. Remote. Sens. 55(2): 894-906 (2017) - [j15]Qingshan Liu, Yubao Sun, Cantian Wang, Tongliang Liu, Dacheng Tao:
Elastic Net Hypergraph Learning for Image Clustering and Semi-Supervised Classification. IEEE Trans. Image Process. 26(1): 452-463 (2017) - [j14]Kede Ma, Wentao Liu, Tongliang Liu, Zhou Wang, Dacheng Tao:
dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs. IEEE Trans. Image Process. 26(8): 3951-3964 (2017) - [j13]Hongfu Liu, Junjie Wu, Tongliang Liu, Dacheng Tao, Yun Fu:
Spectral Ensemble Clustering via Weighted K-Means: Theoretical and Practical Evidence. IEEE Trans. Knowl. Data Eng. 29(5): 1129-1143 (2017) - [j12]Tongliang Liu, Mingming Gong, Dacheng Tao:
Large-Cone Nonnegative Matrix Factorization. IEEE Trans. Neural Networks Learn. Syst. 28(9): 2129-2142 (2017) - [c9]Xiyu Yu, Tongliang Liu, Xinchao Wang, Dacheng Tao:
On Compressing Deep Models by Low Rank and Sparse Decomposition. CVPR 2017: 67-76 - [c8]Tongliang Liu, Gábor Lugosi, Gergely Neu, Dacheng Tao:
Algorithmic Stability and Hypothesis Complexity. ICML 2017: 2159-2167 - [c7]Tongliang Liu, Qiang Yang, Dacheng Tao:
Understanding How Feature Structure Transfers in Transfer Learning. IJCAI 2017: 2365-2371 - [c6]Yong Luo, Yonggang Wen, Tongliang Liu, Dacheng Tao:
General Heterogeneous Transfer Distance Metric Learning via Knowledge Fragments Transfer. IJCAI 2017: 2450-2456 - [i8]Tongliang Liu, Gábor Lugosi, Gergely Neu, Dacheng Tao:
Algorithmic stability and hypothesis complexity. CoRR abs/1702.08712 (2017) - [i7]Jiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao, Dacheng Tao:
Learning with Bounded Instance- and Label-dependent Label Noise. CoRR abs/1709.03768 (2017) - [i6]Xiyu Yu, Tongliang Liu, Mingming Gong, Dacheng Tao:
Learning with Biased Complementary Labels. CoRR abs/1711.09535 (2017) - 2016
- [j11]Tongliang Liu, Dacheng Tao, Dong Xu:
Dimensionality-Dependent Generalization Bounds for k-Dimensional Coding Schemes. Neural Comput. 28(10): 2213-2249 (2016) - [j10]Tongliang Liu, Dacheng Tao:
Classification with Noisy Labels by Importance Reweighting. IEEE Trans. Pattern Anal. Mach. Intell. 38(3): 447-461 (2016) - [j9]Jie Gui, Tongliang Liu, Dacheng Tao, Zhenan Sun, Tieniu Tan:
Representative Vector Machines: A Unified Framework for Classical Classifiers. IEEE Trans. Cybern. 46(8): 1877-1888 (2016) - [j8]Chang Xu, Tongliang Liu, Dacheng Tao, Chao Xu:
Local Rademacher Complexity for Multi-Label Learning. IEEE Trans. Image Process. 25(3): 1495-1507 (2016) - [j7]Hao Xiong, Tongliang Liu, Dacheng Tao, Heng Tao Shen:
Dual Diversified Dynamical Gaussian Process Latent Variable Model for Video Repairing. IEEE Trans. Image Process. 25(8): 3626-3637 (2016) - [j6]Xiaoyan Li, Tongliang Liu, Jiankang Deng, Dacheng Tao:
Video Face Editing Using Temporal-Spatial-Smooth Warping. ACM Trans. Intell. Syst. Technol. 7(3): 32:1-32:28 (2016) - [j5]Tongliang Liu, Dacheng Tao:
On the Performance of Manhattan Nonnegative Matrix Factorization. IEEE Trans. Neural Networks Learn. Syst. 27(9): 1851-1863 (2016) - [c5]Hao Xiong, Tongliang Liu, Dacheng Tao:
Diversified Dynamical Gaussian Process Latent Variable Model for Video Repair. AAAI 2016: 3641-3647 - [c4]Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schölkopf:
Domain Adaptation with Conditional Transferable Components. ICML 2016: 2839-2848 - [i5]Tongliang Liu, Dacheng Tao, Dong Xu:
Dimensionality-Dependent Generalization Bounds for $k$-Dimensional Coding Schemes. CoRR abs/1601.00238 (2016) - [i4]Qingshan Liu, Yubao Sun, Cantian Wang, Tongliang Liu, Dacheng Tao:
Elastic Net Hypergraph Learning for Image Clustering and Semi-supervised Classification. CoRR abs/1603.01096 (2016) - [i3]Kede Ma, Huan Fu, Tongliang Liu, Zhou Wang, Dacheng Tao:
Local Blur Mapping: Exploiting High-Level Semantics by Deep Neural Networks. CoRR abs/1612.01227 (2016) - 2015
- [j4]Yanan Lu, Fengying Xie, Tongliang Liu, Zhiguo Jiang, Dacheng Tao:
No Reference Quality Assessment for Multiply-Distorted Images Based on an Improved Bag-of-Words Model. IEEE Signal Process. Lett. 22(10): 1811-1815 (2015) - [j3]Yong Luo, Tongliang Liu, Dacheng Tao, Chao Xu:
Multiview Matrix Completion for Multilabel Image Classification. IEEE Trans. Image Process. 24(8): 2355-2368 (2015) - [j2]Chen Gong, Tongliang Liu, Dacheng Tao, Keren Fu, Enmei Tu, Jie Yang:
Deformed Graph Laplacian for Semisupervised Learning. IEEE Trans. Neural Networks Learn. Syst. 26(10): 2261-2274 (2015) - [c3]Ya Li, Xinmei Tian, Tongliang Liu, Dacheng Tao:
Multi-Task Model and Feature Joint Learning. IJCAI 2015: 3643-3649 - [c2]Hongfu Liu, Tongliang Liu, Junjie Wu, Dacheng Tao, Yun Fu:
Spectral Ensemble Clustering. KDD 2015: 715-724 - 2014
- [j1]Yong Luo, Tongliang Liu, Dacheng Tao, Chao Xu:
Decomposition-Based Transfer Distance Metric Learning for Image Classification. IEEE Trans. Image Process. 23(9): 3789-3801 (2014) - [c1]Ming Shao, Sheng Li, Tongliang Liu, Dacheng Tao, Thomas S. Huang, Yun Fu:
Learning relative features through adaptive pooling for image classification. ICME 2014: 1-6 - [i2]Chang Xu, Tongliang Liu, Dacheng Tao, Chao Xu:
Local Rademacher Complexity for Multi-label Learning. CoRR abs/1410.6990 (2014) - [i1]Tongliang Liu, Dacheng Tao:
Classification with Noisy Labels by Importance Reweighting. CoRR abs/1411.7718 (2014)
Coauthor Index
[j35] [j33] [j32] [c28] [i47] [i45] [i44] [i41] [i39] [i38] [j30] [j29] [j28] [j26] [j25] [c25] [c21] [i35] [i33] [i32] [i31] [i30] [i29] [i28] [i26] [i25] [i24] [i23] [i21] [i20] [i17] [i16] [j24] [j23] [j22] [j21] [j20] [j19] [j18] [c19] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [j17] [j15] [j14] [j13] [j12] [c9] [c8] [c7] [c6] [i8] [i7] [i6] [j11] [j10] [j9] [j8] [j7] [j6] [j5] [c5] [c4] [i5] [i4] [i3] [j4] [j3] [j2] [c3] [c2] [j1] [c1] [i2] [i1]
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