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ORCIDIvor W. Tsang
Ivor Wai-Hung Tsang
Person information
- affiliation: A*STAR, Singapore
- affiliation: University of Technology Sydney, Australia
- affiliation (2008 - 2014): Nanyang Technological University, Singapore
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Journal Articles
- 2024
[j161]Feiyang Ye
, Baijiong Lin, Zhixiong Yue, Yu Zhang, Ivor W. Tsang:
Multi-objective meta-learning. Artif. Intell. 335: 104184 (2024)- [j160]Xingrui Yu, Bo Han, Ivor W. Tsang:
USN: A Robust Imitation Learning Method against Diverse Action Noise. J. Artif. Intell. Res. 79: 1237-1280 (2024) - [j159]Bowen Xing, Ivor W. Tsang:
Exploiting Contextual Target Attributes for Target Sentiment Classification. J. Artif. Intell. Res. 80: 419-439 (2024) - [j158]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
Generative Adversarial Ranking Nets. J. Mach. Learn. Res. 25: 119:1-119:35 (2024) - [j157]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
Sanitized clustering against confounding bias. Mach. Learn. 113(6): 3711-3730 (2024) - [j156]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
PROUD: PaRetO-gUided diffusion model for multi-objective generation. Mach. Learn. 113(9): 6511-6538 (2024) - [j155]Bowen Xing, Ivor W. Tsang:
Co-Guiding for Multi-Intent Spoken Language Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 46(5): 2965-2980 (2024) - [j154]Bowen Xing, Ivor W. Tsang:
HC$^{2}$2L: Hybrid and Cooperative Contrastive Learning for Cross-Lingual Spoken Language Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 8094-8105 (2024) - [j153]Bohao Qu, Xiaofeng Cao, Yi Chang, Ivor W. Tsang, Yew-Soon Ong:
Diversifying Policies With Non-Markov Dispersion to Expand the Solution Space. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 11392-11408 (2024) - [j152]Xu Chen, Yuangang Pan, Ivor W. Tsang, Ya Zhang:
Learning node representations against perturbations. Pattern Recognit. 145: 109976 (2024) - [j151]Mengxi Jiang, Yulei Sui, Yunqi Lei, Xiaofei Xie, Cuihua Li, Yang Liu, Ivor W. Tsang:
Adversarial Learning for Coordinate Regression Through $k$k-Layer Penetrating Representation. IEEE Trans. Dependable Secur. Comput. 21(6): 5538-5552 (2024) - [j150]Joey Tianyi Zhou, Ivor W. Tsang, Yew Soon Ong:
Guest Editorial Special Issue on Resource Sustainable Computational and Artificial Intelligence. IEEE Trans. Emerg. Top. Comput. Intell. 8(5): 3196-3198 (2024) - [j149]Yu Wang, Liang Hu, Xiaofeng Cao, Yi Chang, Ivor W. Tsang:
Enhancing Locally Adaptive Smoothing of Graph Neural Networks Via Laplacian Node Disagreement. IEEE Trans. Knowl. Data Eng. 36(3): 1099-1112 (2024) - [j148]Bohao Qu, Xiaofeng Cao, Qing Guo, Yi Chang, Ivor W. Tsang, Chengqi Zhang:
Transductive Reward Inference on Graph. IEEE Trans. Knowl. Data Eng. 36(11): 7217-7228 (2024) - [j147]Yuze Tan, Yixi Liu, Hongjie Wu, Shudong Huang, Zenglin Xu, Ivor W. Tsang, Jiancheng Lv:
Euclidean Distance is Not Your Swiss Army Knife. IEEE Trans. Knowl. Data Eng. 36(12): 8179-8191 (2024) - [j146]Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao:
Differential-Critic GAN: Generating What You Want by a Cue of Preferences. IEEE Trans. Neural Networks Learn. Syst. 35(3): 3754-3768 (2024) - [j145]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
CGDD: Multiview Graph Clustering via Cross-Graph Diversity Detection. IEEE Trans. Neural Networks Learn. Syst. 35(3): 4206-4219 (2024) - [j144]Peiyao Zhao, Yuangang Pan, Xin Li, Xu Chen, Ivor W. Tsang, Lejian Liao:
Coarse-to-Fine Contrastive Learning on Graphs. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4622-4634 (2024) - [j143]Maosen Li, Siheng Chen, Yanning Shen, Genjia Liu, Ivor W. Tsang, Ya Zhang:
Online Multi-Agent Forecasting With Interpretable Collaborative Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4768-4782 (2024) - [j142]Defu Liu, Ivor W. Tsang, Guowu Yang:
A Convergence Path to Deep Learning on Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. 35(4): 5170-5182 (2024) - [j141]Boyuan Zheng, Sunny Verma, Jianlong Zhou, Ivor W. Tsang, Fang Chen:
Imitation Learning: Progress, Taxonomies and Challenges. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6322-6337 (2024) - [j140]Xiaofeng Cao, Ivor W. Tsang:
Distribution Matching for Machine Teaching. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12316-12329 (2024) - [j139]Jing Li, Yuangang Pan, Ivor W. Tsang:
Taming Overconfident Prediction on Unlabeled Data From Hindsight. IEEE Trans. Neural Networks Learn. Syst. 35(10): 14151-14163 (2024) - 2023
- [j138]Xiaowei Zhou, Ivor W. Tsang, Jie Yin:
LADDER: Latent boundary-guided adversarial training. Mach. Learn. 112(10): 3851-3879 (2023) - [j137]Jiangchao Yao, Bo Han, Zhihan Zhou, Ya Zhang, Ivor W. Tsang:
Latent Class-Conditional Noise Model. IEEE Trans. Pattern Anal. Mach. Intell. 45(8): 9964-9980 (2023) - [j136]Yongshun Gong, Zhibin Li, Wei Liu, Xiankai Lu, Xinwang Liu, Ivor W. Tsang, Yilong Yin:
Missingness-Pattern-Adaptive Learning With Incomplete Data. IEEE Trans. Pattern Anal. Mach. Intell. 45(9): 11053-11066 (2023) - [j135]Jing Li, Yuangang Pan, Yueming Lyu, Yinghua Yao, Yulei Sui, Ivor W. Tsang:
Earning Extra Performance From Restrictive Feedbacks. IEEE Trans. Pattern Anal. Mach. Intell. 45(10): 11753-11765 (2023) - [j134]Bowen Xing, Ivor W. Tsang:
Relational Temporal Graph Reasoning for Dual-Task Dialogue Language Understanding. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13170-13184 (2023) - [j133]Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang:
Data-Efficient Learning via Minimizing Hyperspherical Energy. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13422-13437 (2023) - [j132]Defu Liu, Wen Li, Lixin Duan, Ivor W. Tsang, Guowu Yang:
Noisy Label Learning With Provable Consistency for a Wider Family of Losses. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13536-13552 (2023) - [j131]Bing Li, Wei Cui, Le Zhang, Ce Zhu, Wei Wang, Ivor W. Tsang, Joey Tianyi Zhou:
DifFormer: Multi-Resolutional Differencing Transformer With Dynamic Ranging for Time Series Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 13586-13598 (2023) - [j130]Yuhao Liu, Qing Guo, Lan Fu, Zhanghan Ke, Ke Xu, Wei Feng, Ivor W. Tsang, Rynson W. H. Lau:
Structure-Informed Shadow Removal Networks. IEEE Trans. Image Process. 32: 5823-5836 (2023) - [j129]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Latent Representation Guided Multi-View Clustering. IEEE Trans. Knowl. Data Eng. 35(7): 7082-7087 (2023) - [j128]Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
A Multi-View Multi-Task Learning Framework for Multi-Variate Time Series Forecasting. IEEE Trans. Knowl. Data Eng. 35(8): 7665-7680 (2023) - [j127]Hui Xu, Changyu Li, Yan Zhang, Lixin Duan, Ivor W. Tsang, Jie Shao:
MetaCAR: Cross-Domain Meta-Augmentation for Content-Aware Recommendation. IEEE Trans. Knowl. Data Eng. 35(8): 8199-8212 (2023) - [j126]Shudong Huang, Yixi Liu, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Multi-View Subspace Clustering by Joint Measuring of Consistency and Diversity. IEEE Trans. Knowl. Data Eng. 35(8): 8270-8281 (2023) - [j125]Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya Zhang, Hao Zhang, Ivor W. Tsang, Jingren Zhou, Mingyuan Zhou:
Contrastive Attraction and Contrastive Repulsion for Representation Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j124]Yiming Xu, Lin Chen, Lixin Duan, Ivor W. Tsang, Jiebo Luo:
Open Set Domain Adaptation With Soft Unknown-Class Rejection. IEEE Trans. Neural Networks Learn. Syst. 34(3): 1601-1612 (2023) - [j123]Xu Chen, Ya Zhang, Ivor W. Tsang, Yuangang Pan, Jingchao Su:
Toward Equivalent Transformation of User Preferences in Cross Domain Recommendation. ACM Trans. Inf. Syst. 41(1): 14:1-14:31 (2023) - 2022
- [j122]Bowen Xing, Ivor W. Tsang:
Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis. J. Artif. Intell. Res. 74: 627-659 (2022) - [j121]Xi Peng, Yunfan Li, Ivor W. Tsang, Hongyuan Zhu, Jiancheng Lv, Joey Tianyi Zhou:
XAI Beyond Classification: Interpretable Neural Clustering. J. Mach. Learn. Res. 23: 6:1-6:28 (2022) - [j120]Yuangang Pan, Ivor W. Tsang, Weijie Chen, Gang Niu, Masashi Sugiyama:
Fast and Robust Rank Aggregation against Model Misspecification. J. Mach. Learn. Res. 23: 23:1-23:35 (2022) - [j119]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Multiple partitions alignment via spectral rotation. Mach. Learn. 111(3): 1049-1072 (2022) - [j118]Xu Chen, Siheng Chen, Jiangchao Yao, Huangjie Zheng, Ya Zhang, Ivor W. Tsang:
Learning on Attribute-Missing Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 44(2): 740-757 (2022) - [j117]Yang Zhang, Ivor W. Tsang, Yawei Luo, Changhui Hu, Xiaobo Lu, Xin Yu:
Recursive Copy and Paste GAN: Face Hallucination From Shaded Thumbnails. IEEE Trans. Pattern Anal. Mach. Intell. 44(8): 4321-4338 (2022) - [j116]Xiaofeng Cao, Ivor W. Tsang:
Distribution Disagreement via Lorentzian Focal Representation. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6872-6889 (2022) - [j115]Weiwei Liu, Haobo Wang, Xiaobo Shen, Ivor W. Tsang:
The Emerging Trends of Multi-Label Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(11): 7955-7974 (2022) - [j114]Shudong Huang, Wei Shi, Zenglin Xu, Ivor W. Tsang, Jiancheng Lv:
Efficient federated multi-view learning. Pattern Recognit. 131: 108817 (2022) - [j113]Xiaofeng Cao, Ivor W. Tsang, Jianliang Xu:
Cold-Start Active Sampling Via γ-Tube. IEEE Trans. Cybern. 52(7): 6034-6045 (2022) - [j112]Bowen Xing, Ivor W. Tsang:
Understand Me, if You Refer to Aspect Knowledge: Knowledge-Aware Gated Recurrent Memory Network. IEEE Trans. Emerg. Top. Comput. Intell. 6(5): 1092-1102 (2022) - [j111]Liang Feng, Yuxiao Huang, Ivor W. Tsang, Abhishek Gupta, Ke Tang, Kay Chen Tan, Yew-Soon Ong:
Towards Faster Vehicle Routing by Transferring Knowledge From Customer Representation. IEEE Trans. Intell. Transp. Syst. 23(2): 952-965 (2022) - [j110]Yan Zhang, Ivor W. Tsang, Hongzhi Yin, Guowu Yang, Defu Lian, Jingjing Li:
Deep Pairwise Hashing for Cold-Start Recommendation. IEEE Trans. Knowl. Data Eng. 34(7): 3169-3181 (2022) - [j109]Huiting Hong, Xin Li, Yuangang Pan, Ivor W. Tsang:
Domain-Adversarial Network Alignment. IEEE Trans. Knowl. Data Eng. 34(7): 3211-3224 (2022) - [j108]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Measuring Diversity in Graph Learning: A Unified Framework for Structured Multi-View Clustering. IEEE Trans. Knowl. Data Eng. 34(12): 5869-5883 (2022) - [j107]Baijiong Lin, Feiyang Ye, Yu Zhang, Ivor W. Tsang:
Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning. Trans. Mach. Learn. Res. 2022 (2022) - [j106]Xiaobo Shen, Guohua Dong, Yuhui Zheng, Long Lan, Ivor W. Tsang, Quan-Sen Sun:
Deep Co-Image-Label Hashing for Multi-Label Image Retrieval. IEEE Trans. Multim. 24: 1116-1126 (2022) - [j105]Xiaofeng Cao, Ivor W. Tsang:
Shattering Distribution for Active Learning. IEEE Trans. Neural Networks Learn. Syst. 33(1): 215-228 (2022) - [j104]Jing Chai, Ivor W. Tsang:
Learning With Label Proportions by Incorporating Unmarked Data. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5898-5912 (2022) - 2021
- [j103]Yuangang Pan, Ivor W. Tsang, Yueming Lyu, Avinash Kumar Singh, Chin-Teng Lin:
Online Mental Fatigue Monitoring via Indirect Brain Dynamics Evaluation. Neural Comput. 33(6): 1616-1655 (2021) - [j102]Xiaofeng Xu, Ivor W. Tsang, Chuancai Liu:
Complementary Attributes: A New Clue to Zero-Shot Learning. IEEE Trans. Cybern. 51(3): 1519-1530 (2021) - [j101]Yang Zhang, Ivor W. Tsang, Jun Li, Ping Liu, Xiaobo Lu, Xin Yu:
Face Hallucination With Finishing Touches. IEEE Trans. Image Process. 30: 1728-1743 (2021) - [j100]Jinliang Deng, Xiusi Chen, Zipei Fan, Renhe Jiang, Xuan Song, Ivor W. Tsang:
The Pulse of Urban Transport: Exploring the Co-evolving Pattern for Spatio-temporal Forecasting. ACM Trans. Knowl. Discov. Data 15(6): 103:1-103:25 (2021) - [j99]Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen, Sai-Fu Fung, Celina Ping Yu:
Privacy-Preserving Stochastic Gradual Learning. IEEE Trans. Knowl. Data Eng. 33(8): 3129-3140 (2021) - 2020
- [j98]Yan Zhang, Ivor W. Tsang, Lixin Duan:
Collaborative Generative Hashing for Marketing and Fast Cold-Start Recommendation. IEEE Intell. Syst. 35(5): 84-95 (2020) - [j97]Shudong Huang, Zenglin Xu, Ivor W. Tsang, Zhao Kang:
Auto-weighted multi-view co-clustering with bipartite graphs. Inf. Sci. 512: 18-30 (2020) - [j96]Xiaofeng Xu, Ivor W. Tsang, Chuancai Liu:
Improving Generalization via Attribute Selection on Out-of-the-Box Data. Neural Comput. 32(2): 485-514 (2020) - [j95]Yuangang Pan, Ivor W. Tsang, Avinash Kumar Singh, Chin-Teng Lin, Masashi Sugiyama:
Stochastic Multichannel Ranking with Brain Dynamics Preferences. Neural Comput. 32(8): 1499-1530 (2020) - [j94]Yaxin Shi, Yuangang Pan, Donna Xu, Ivor W. Tsang:
Multiview Alignment and Generation in CCA via Consistent Latent Encoding. Neural Comput. 32(10): 1936-1979 (2020) - [j93]Biswajeet Pradhan, Husam Abdulrasool H. Al-Najjar, Maher Ibrahim Sameen, Ivor W. Tsang, Abdullah M. Alamri:
Unseen Land Cover Classification from High-Resolution Orthophotos Using Integration of Zero-Shot Learning and Convolutional Neural Networks. Remote. Sens. 12(10): 1676 (2020) - [j92]Yanxin Zhang, Yulei Sui, Shirui Pan, Zheng Zheng, Baodi Ning, Ivor W. Tsang, Wanlei Zhou:
Familial Clustering for Weakly-Labeled Android Malware Using Hybrid Representation Learning. IEEE Trans. Inf. Forensics Secur. 15: 3401-3414 (2020) - [j91]Jing Li, Yuangang Pan, Yulei Sui, Ivor W. Tsang:
Secure Metric Learning via Differential Pairwise Privacy. IEEE Trans. Inf. Forensics Secur. 15: 3640-3652 (2020) - [j90]Fanhua Shang, Kaiwen Zhou, Hongying Liu, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao, Licheng Jiao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. IEEE Trans. Knowl. Data Eng. 32(1): 188-202 (2020) - [j89]Yan Yan, Mingkui Tan, Ivor W. Tsang, Yi Yang, Qinfeng Shi, Chengqi Zhang:
Fast and Low Memory Cost Matrix Factorization: Algorithm, Analysis, and Case Study. IEEE Trans. Knowl. Data Eng. 32(2): 288-301 (2020) - [j88]Weiwei Liu, Xiaobo Shen, Yew-Soon Ong, Ivor W. Tsang, Chen Gong, Vladimir Pavlovic:
Guest Editorial Special Issue on Structured Multi-Output Learning: Modeling, Algorithm, Theory, and Applications. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2236-2239 (2020) - [j87]Donna Xu, Yaxin Shi, Ivor W. Tsang, Yew-Soon Ong, Chen Gong, Xiaobo Shen:
Survey on Multi-Output Learning. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2409-2429 (2020) - [j86]Jing Chai, Ivor W. Tsang, Weijie Chen:
Large Margin Partial Label Machine. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2594-2608 (2020) - 2019
- [j85]Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang:
A deep learning framework for Hybrid Heterogeneous Transfer Learning. Artif. Intell. 275: 310-328 (2019) - [j84]Donna Xu, Ivor W. Tsang, Eng K. Chew, Cosimo Siclari, Varun Kaul:
A Data-Analytics Approach for Enterprise Resilience. IEEE Intell. Syst. 34(3): 6-18 (2019) - [j83]Joey Tianyi Zhou, Ivor W. Tsang, Sinno Jialin Pan, Mingkui Tan:
Multi-class Heterogeneous Domain Adaptation. J. Mach. Learn. Res. 20: 57:1-57:31 (2019) - [j82]Joey Tianyi Zhou, Ivor W. Tsang, Shen-Shyang Ho, Klaus-Robert Müller:
N-ary decomposition for multi-class classification. Mach. Learn. 108(5): 809-830 (2019) - [j81]Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama:
Millionaire: a hint-guided approach for crowdsourcing. Mach. Learn. 108(5): 831-858 (2019) - [j80]Weiwei Liu, Donna Xu, Ivor W. Tsang, Wenjie Zhang:
Metric Learning for Multi-Output Tasks. IEEE Trans. Pattern Anal. Mach. Intell. 41(2): 408-422 (2019) - [j79]Shudong Huang, Zhao Kang, Ivor W. Tsang, Zenglin Xu:
Auto-weighted multi-view clustering via kernelized graph learning. Pattern Recognit. 88: 174-184 (2019) - [j78]Chao Ma, Ivor W. Tsang, Fumin Shen, Chuancai Liu:
Error Correcting Input and Output Hashing. IEEE Trans. Cybern. 49(3): 781-791 (2019) - [j77]Shaukat R. Abidi, Massimo Piccardi, Ivor W. Tsang, Mary-Anne Williams:
Well-M3N: A Maximum-Margin Approach to Unsupervised Structured Prediction. IEEE Trans. Emerg. Top. Comput. Intell. 3(6): 427-439 (2019) - [j76]Xuanyi Dong, Yan Yan, Mingkui Tan, Yi Yang, Ivor W. Tsang:
Late Fusion via Subspace Search With Consistency Preservation. IEEE Trans. Image Process. 28(1): 518-528 (2019) - [j75]Weiwei Liu, Xiaobo Shen, Bo Du, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin:
Hyperspectral Imagery Classification via Stochastic HHSVMs. IEEE Trans. Image Process. 28(2): 577-588 (2019) - [j74]Jiangchao Yao, Jiajie Wang, Ivor W. Tsang, Ya Zhang, Jun Sun, Chengqi Zhang, Rui Zhang:
Deep Learning From Noisy Image Labels With Quality Embedding. IEEE Trans. Image Process. 28(4): 1909-1922 (2019) - [j73]Wan-Yu Deng, Amaury Lendasse, Yew-Soon Ong, Ivor Wai-Hung Tsang, Lin Chen, Qing-Hua Zheng:
Domain Adaption via Feature Selection on Explicit Feature Map. IEEE Trans. Neural Networks Learn. Syst. 30(4): 1180-1190 (2019) - [j72]Bo Han, Ivor W. Tsang, Ling Chen, Joey Tianyi Zhou, Celina Ping Yu:
Beyond Majority Voting: A Coarse-to-Fine Label Filtration for Heavily Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. 30(12): 3774-3787 (2019) - 2018
- [j71]Bo Han, Yuangang Pan, Ivor W. Tsang:
Robust Plackett-Luce model for k-ary crowdsourced preferences. Mach. Learn. 107(4): 675-702 (2018) - [j70]Yuangang Pan, Bo Han, Ivor W. Tsang:
Stagewise learning for noisy k-ary preferences. Mach. Learn. 107(8-10): 1333-1361 (2018) - [j69]Sharath Chandra Guntuku, Joey Tianyi Zhou, Sujoy Roy, Weisi Lin, Ivor W. Tsang:
'Who Likes What and, Why?' Insights into Modeling Users' Personality Based on Image 'Likes'. IEEE Trans. Affect. Comput. 9(1): 130-143 (2018) - [j68]Donna Xu, Ivor W. Tsang, Ying Zhang:
Online Product Quantization. IEEE Trans. Knowl. Data Eng. 30(11): 2185-2198 (2018) - [j67]Yuguang Yan, Qingyao Wu, Mingkui Tan, Michael K. Ng, Huaqing Min, Ivor W. Tsang:
Online Heterogeneous Transfer by Hedge Ensemble of Offline and Online Decisions. IEEE Trans. Neural Networks Learn. Syst. 29(7): 3252-3263 (2018) - [j66]Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong:
Multilabel Prediction via Cross-View Search. IEEE Trans. Neural Networks Learn. Syst. 29(9): 4324-4338 (2018) - [j65]Bo Han, Ivor W. Tsang, Ling Chen, Celina Ping Yu, Sai-Fu Fung:
Progressive Stochastic Learning for Noisy Labels. IEEE Trans. Neural Networks Learn. Syst. 29(10): 5136-5148 (2018) - 2017
- [j64]Weiwei Liu, Ivor W. Tsang:
Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions. J. Mach. Learn. Res. 18: 81:1-81:36 (2017) - [j63]Weiwei Liu, Ivor W. Tsang, Klaus-Robert Müller:
An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels. J. Mach. Learn. Res. 18: 94:1-94:38 (2017) - [j62]Qi Mao, Li Wang, Ivor W. Tsang:
A unified probabilistic framework for robust manifold learning and embedding. Mach. Learn. 106(5): 627-650 (2017) - [j61]Qi Mao, Li Wang, Ivor W. Tsang, Yijun Sun:
Principal Graph and Structure Learning Based on Reversed Graph Embedding. IEEE Trans. Pattern Anal. Mach. Intell. 39(11): 2227-2241 (2017) - [j60]Jim Jing-Yan Wang, Ivor Wai-Hung Tsang, Xuefeng Cui, Zhiwu Lu, Xin Gao:
Multi-instance dictionary learning via multivariate performance measure optimization. Pattern Recognit. 66: 448-459 (2017) - [j59]Chao Ma, Ivor W. Tsang, Furong Peng, Chuancai Liu:
Partial Hash Update via Hamming Subspace Learning. IEEE Trans. Image Process. 26(4): 1939-1951 (2017) - [j58]Haishuai Wang, Peng Zhang, Xingquan Zhu, Ivor Wai-Hung Tsang, Ling Chen, Chengqi Zhang, Xindong Wu:
Incremental Subgraph Feature Selection for Graph Classification. IEEE Trans. Knowl. Data Eng. 29(1): 128-142 (2017) - 2016
- [j57]Iti Chaturvedi, Yew-Soon Ong, Ivor W. Tsang, Roy E. Welsch, Erik Cambria:
Learning word dependencies in text by means of a deep recurrent belief network. Knowl. Based Syst. 108: 144-154 (2016) - [j56]Xinxing Xu, Wen Li, Dong Xu, Ivor W. Tsang:
Co-Labeling for Multi-View Weakly Labeled Learning. IEEE Trans. Pattern Anal. Mach. Intell. 38(6): 1113-1125 (2016) - [j55]Yiteng Zhai, Yew-Soon Ong, Ivor W. Tsang:
Making Trillion Correlations Feasible in Feature Grouping and Selection. IEEE Trans. Pattern Anal. Mach. Intell. 38(12): 2472-2486 (2016) - [j54]Shenghua Gao, Lixin Duan, Ivor W. Tsang:
DEFEATnet - A Deep Conventional Image Representation for Image Classification. IEEE Trans. Circuits Syst. Video Technol. 26(3): 494-505 (2016) - [j53]Sharath Chandra Guntuku, Joey Tianyi Zhou, Sujoy Roy, Weisi Lin, Ivor W. Tsang:
Understanding Deep Representations Learned in Modeling Users Likes. IEEE Trans. Image Process. 25(8): 3762-3774 (2016) - 2015
- [j52]Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Ivor W. Tsang:
Memes as building blocks: a case study on evolutionary optimization + transfer learning for routing problems. Memetic Comput. 7(3): 159-180 (2015) - [j51]Liang Feng, Yew-Soon Ong, Meng-Hiot Lim, Ivor W. Tsang:
Memetic Search With Interdomain Learning: A Realization Between CVRP and CARP. IEEE Trans. Evol. Comput. 19(5): 644-658 (2015) - [j50]Marcus Chen, Ivor W. Tsang, Mingkui Tan, Cham Tat Jen:
A Unified Feature Selection Framework for Graph Embedding on High Dimensional Data. IEEE Trans. Knowl. Data Eng. 27(6): 1465-1477 (2015) - [j49]Qi Mao, Ivor W. Tsang, Shenghua Gao, Li Wang:
Generalized Multiple Kernel Learning With Data-Dependent Priors. IEEE Trans. Neural Networks Learn. Syst. 26(6): 1134-1148 (2015) - [j48]Mingkui Tan, Ivor W. Tsang, Li Wang:
Matching Pursuit LASSO Part I: Sparse Recovery Over Big Dictionary. IEEE Trans. Signal Process. 63(3): 727-741 (2015) - [j47]Mingkui Tan, Ivor W. Tsang, Li Wang:
Matching Pursuit LASSO Part II: Applications and Sparse Recovery Over Batch Signals. IEEE Trans. Signal Process. 63(3): 742-753 (2015) - 2014
- [j46]Yiteng Zhai, Yew-Soon Ong, Ivor W. Tsang:
The Emerging ?Big Dimensionality? IEEE Comput. Intell. Mag. 9(3): 14-26 (2014) - [j45]Mingkui Tan, Ivor W. Tsang, Li Wang:
Towards ultrahigh dimensional feature selection for big data. J. Mach. Learn. Res. 15(1): 1371-1429 (2014) - [j44]Wen Li, Lixin Duan, Dong Xu, Ivor W. Tsang:
Learning With Augmented Features for Supervised and Semi-Supervised Heterogeneous Domain Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 36(6): 1134-1148 (2014) - [j43]Zhixiang Ren, Shenghua Gao, Liang-Tien Chia, Ivor Wai-Hung Tsang:
Region-Based Saliency Detection and Its Application in Object Recognition. IEEE Trans. Circuits Syst. Video Technol. 24(5): 769-779 (2014) - [j42]Lin Chen, Dong Xu, Ivor Wai-Hung Tsang, Xuelong Li:
Spectral Embedded Hashing for Scalable Image Retrieval. IEEE Trans. Cybern. 44(7): 1180-1190 (2014) - [j41]Shenghua Gao, Ivor Wai-Hung Tsang, Yi Ma:
Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization. IEEE Trans. Image Process. 23(2): 623-634 (2014) - [j40]Shenghua Gao, Liang-Tien Chia, Ivor Wai-Hung Tsang, Zhixiang Ren:
Concurrent Single-Label Image Classification and Annotation via Efficient Multi-Layer Group Sparse Coding. IEEE Trans. Multim. 16(3): 762-771 (2014) - 2013
- [j39]Yufeng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou:
Convex and scalable weakly labeled SVMs. J. Mach. Learn. Res. 14(1): 2151-2188 (2013) - [j38]Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia:
Laplacian Sparse Coding, Hypergraph Laplacian Sparse Coding, and Applications. IEEE Trans. Pattern Anal. Mach. Intell. 35(1): 92-104 (2013) - [j37]Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
Discovering Low-Rank Shared Concept Space for Adapting Text Mining Models. IEEE Trans. Pattern Anal. Mach. Intell. 35(6): 1284-1297 (2013) - [j36]Nan Li, Ivor W. Tsang, Zhi-Hua Zhou:
Efficient Optimization of Performance Measures by Classifier Adaptation. IEEE Trans. Pattern Anal. Mach. Intell. 35(6): 1370-1382 (2013) - [j35]Qi Mao, Ivor Wai-Hung Tsang:
A Feature Selection Method for Multivariate Performance Measures. IEEE Trans. Pattern Anal. Mach. Intell. 35(9): 2051-2063 (2013) - [j34]Chun-Wei Seah, Yew-Soon Ong, Ivor W. Tsang:
Combating Negative Transfer From Predictive Distribution Differences. IEEE Trans. Cybern. 43(4): 1153-1165 (2013) - [j33]Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia:
Sparse Representation With Kernels. IEEE Trans. Image Process. 22(2): 423-434 (2013) - [j32]Qi Mao, Ivor Wai-Hung Tsang, Shenghua Gao:
Objective-Guided Image Annotation. IEEE Trans. Image Process. 22(4): 1585-1597 (2013) - [j31]Qi Mao, Ivor Wai-Hung Tsang:
Efficient Multitemplate Learning for Structured Prediction. IEEE Trans. Neural Networks Learn. Syst. 24(2): 248-261 (2013) - [j30]Xinxing Xu, Ivor W. Tsang, Dong Xu:
Soft Margin Multiple Kernel Learning. IEEE Trans. Neural Networks Learn. Syst. 24(5): 749-761 (2013) - [j29]Mingkui Tan, Ivor W. Tsang, Li Wang:
Minimax Sparse Logistic Regression for Very High-Dimensional Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 24(10): 1609-1622 (2013) - [j28]Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong:
Transfer Ordinal Label Learning. IEEE Trans. Neural Networks Learn. Syst. 24(11): 1863-1876 (2013) - 2012
- [j27]Shukai Li, Ivor W. Tsang, Narendra S. Chaudhari:
Relevance vector machine based infinite decision agent ensemble learning for credit risk analysis. Expert Syst. Appl. 39(5): 4947-4953 (2012) - [j26]Lixin Duan, Ivor W. Tsang, Dong Xu:
Domain Transfer Multiple Kernel Learning. IEEE Trans. Pattern Anal. Mach. Intell. 34(3): 465-479 (2012) - [j25]Lixin Duan, Dong Xu, Ivor Wai-Hung Tsang, Jiebo Luo:
Visual Event Recognition in Videos by Learning from Web Data. IEEE Trans. Pattern Anal. Mach. Intell. 34(9): 1667-1680 (2012) - [j24]Lin Chen, Dong Xu, Ivor W. Tsang, Jiebo Luo:
Tag-Based Image Retrieval Improved by Augmented Features and Group-Based Refinement. IEEE Trans. Multim. 14(4): 1057-1067 (2012) - [j23]Lixin Duan, Dong Xu, Ivor Wai-Hung Tsang:
Domain Adaptation From Multiple Sources: A Domain-Dependent Regularization Approach. IEEE Trans. Neural Networks Learn. Syst. 23(3): 504-518 (2012) - [j22]Lin Chen, Ivor W. Tsang, Dong Xu:
Laplacian Embedded Regression for Scalable Manifold Regularization. IEEE Trans. Neural Networks Learn. Syst. 23(6): 902-915 (2012) - [j21]Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong:
Transductive Ordinal Regression. IEEE Trans. Neural Networks Learn. Syst. 23(7): 1074-1086 (2012) - 2011
- [j20]William-Chandra Tjhi, Gary Kee Khoon Lee, Terence Hung, Ivor Wai-Hung Tsang, Yew-Soon Ong, Frédéric Bard, Victor Racine:
Exploratory analysis of cell-based screening data for phenotype identification in drug-siRNA study. Int. J. Comput. Biol. Drug Des. 4(2): 194-215 (2011) - [j19]Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi:
A Family of Simple Non-Parametric Kernel Learning Algorithms. J. Mach. Learn. Res. 12: 1313-1347 (2011) - [j18]Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo:
Textual Query of Personal Photos Facilitated by Large-Scale Web Data. IEEE Trans. Pattern Anal. Mach. Intell. 33(5): 1022-1036 (2011) - [j17]Lixin Duan, Wen Li, Ivor Wai-Hung Tsang, Dong Xu:
Improving Web Image Search by Bag-Based Reranking. IEEE Trans. Image Process. 20(11): 3280-3290 (2011) - [j16]Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qiang Yang:
Domain Adaptation via Transfer Component Analysis. IEEE Trans. Neural Networks 22(2): 199-210 (2011) - [j15]Feiping Nie, Zinan Zeng, Ivor W. Tsang, Dong Xu, Changshui Zhang:
Spectral Embedded Clustering: A Framework for In-Sample and Out-of-Sample Spectral Clustering. IEEE Trans. Neural Networks 22(11): 1796-1808 (2011) - [j14]Shutao Li, Mingkui Tan, Ivor W. Tsang, James Tin-Yau Kwok:
A Hybrid PSO-BFGS Strategy for Global Optimization of Multimodal Functions. IEEE Trans. Syst. Man Cybern. Part B 41(4): 1003-1014 (2011) - 2010
- [j13]Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changshui Zhang:
Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction. IEEE Trans. Image Process. 19(7): 1921-1932 (2010) - [j12]Wenliang Zhong, Weike Pan, James T. Kwok, Ivor W. Tsang:
Incorporating the loss function into discriminative clustering of structured outputs. IEEE Trans. Neural Networks 21(10): 1564-1575 (2010) - 2009
- [j11]Brian Kan-Wing Mak, Tsz-Chung Lai, Ivor W. Tsang, James Tin-Yau Kwok:
Maximum Penalized Likelihood Kernel Regression for Fast Adaptation. IEEE Trans. Speech Audio Process. 17(7): 1372-1381 (2009) - [j10]Kai Zhang, Ivor W. Tsang, James T. Kwok:
Maximum Margin Clustering Made Practical. IEEE Trans. Neural Networks 20(4): 583-596 (2009) - 2008
- [j9]Ivor Wai-Hung Tsang, András Kocsor, James Tin-Yau Kwok:
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines. IEEE Trans. Neural Networks 19(4): 610-624 (2008) - 2007
- [j8]Jooyoung Park, Daesung Kang, Jongho Kim, James T. Kwok, Ivor W. Tsang:
SVDD-Based Pattern Denoising. Neural Comput. 19(7): 1919-1938 (2007) - [j7]James T. Kwok, Ivor Wai-Hung Tsang, Jacek M. Zurada:
A Class of Single-Class Minimax Probability Machines for Novelty Detection. IEEE Trans. Neural Networks 18(3): 778-785 (2007) - 2006
- [j6]Ivor Wai-Hung Tsang, James Tin-Yau Kwok:
Efficient hyperkernel learning using second-order cone programming. IEEE Trans. Neural Networks 17(1): 48-58 (2006) - [j5]Ivor Wai-Hung Tsang, James Tin-Yau Kwok, Jacek M. Zurada:
Generalized Core Vector Machines. IEEE Trans. Neural Networks 17(5): 1126-1140 (2006) - 2005
- [j4]Ivor W. Tsang, James T. Kwok, Pak-Ming Cheung:
Core Vector Machines: Fast SVM Training on Very Large Data Sets. J. Mach. Learn. Res. 6: 363-392 (2005) - 2004
- [j3]James Tin-Yau Kwok, Ivor Wai-Hung Tsang:
The pre-image problem in kernel methods. IEEE Trans. Neural Networks 15(6): 1517-1525 (2004) - [j2]Shutao Li, James Tin-Yau Kwok, Ivor Wai-Hung Tsang, Yaonan Wang:
Fusing images with different focuses using support vector machines. IEEE Trans. Neural Networks 15(6): 1555-1561 (2004) - 2003
- [j1]James T. Kwok, Ivor W. Tsang:
Linear dependency between ε and the input noise in ε-support vector regression. IEEE Trans. Neural Networks 14(3): 544-553 (2003)
Conference and Workshop Papers
- 2024
- [c153]Sixing Yan, William K. Cheung, Ivor W. Tsang, Keith Chin, Terence M. Tong, Ka Chun Cheung, Simon See:
AHIVE: Anatomy-Aware Hierarchical Vision Encoding for Interactive Radiology Report Retrieval. CVPR 2024: 14324-14333 - [c152]Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang:
A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. ECAI 2024: 2621-2628 - [c151]Sensen Gao, Xiaojun Jia, Xuhong Ren, Ivor W. Tsang, Qing Guo:
Boosting Transferability in Vision-Language Attacks via Diversification Along the Intersection Region of Adversarial Trajectory. ECCV (57) 2024: 442-460 - [c150]Bowen Xing, Lizi Liao, Minlie Huang, Ivor W. Tsang:
DC-Instruct: An Effective Framework for Generative Multi-intent Spoken Language Understanding. EMNLP 2024: 14520-14534 - [c149]Yang He, Lingao Xiao, Joey Tianyi Zhou, Ivor W. Tsang:
Multisize Dataset Condensation. ICLR 2024 - [c148]Feng Hong, Jiangchao Yao, Yueming Lyu, Zhihan Zhou, Ivor W. Tsang, Ya Zhang, Yanfeng Wang:
On Harmonizing Implicit Subpopulations. ICLR 2024 - [c147]Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor W. Tsang, Yong Liu:
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold. ICLR 2024 - [c146]Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang, Yang Liu, Qing Guo:
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks. ICLR 2024 - [c145]Cheng Chen, Ivor W. Tsang:
Self-Teaching Prompting for Multi-Intent Learning with Limited Supervision. Tiny Papers @ ICLR 2024 - [c144]Feiyang Ye, Yueming Lyu, Xuehao Wang, Yu Zhang, Ivor W. Tsang:
Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning. ICLR 2024 - [c143]Feng Hong, Yueming Lyu, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Yanfeng Wang:
Diversified Batch Selection for Training Acceleration. ICML 2024 - [c142]Hao Di, Haishan Ye, Xiangyu Chang, Guang Dai, Ivor W. Tsang:
Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods. ICML 2024 - [c141]Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai, Ivor W. Tsang:
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient. ICML 2024 - [c140]Yilong Wang, Haishan Ye, Guang Dai, Ivor W. Tsang:
Can Gaussian Sketching Converge Faster on a Preconditioned Landscape? ICML 2024 - [c139]Xingfeng Li, Yuangang Pan, Yinghui Sun, Quansen Sun, Ivor W. Tsang, Zhenwen Ren:
Fast Unpaired Multi-view Clustering. IJCAI 2024: 4488-4496 - [c138]Kairui Hu, Ming Yan, Wen Haw Chong, Yong Keong Yap, Cuntai Guan, Joey Tianyi Zhou, Ivor W. Tsang:
Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection. IJCNN 2024: 1-8 - [c137]Xiaoting Lyu, Yufei Han, Wei Wang, Hangwei Qian, Ivor W. Tsang, Xiangliang Zhang:
Cross-Context Backdoor Attacks against Graph Prompt Learning. KDD 2024: 2094-2105 - [c136]Sixing Yan, Haiyan Yin, Ivor W. Tsang, William K. Cheung:
Diagnose with Uncertainty Awareness: Diagnostic Uncertainty Encoding Framework for Radiology Report Generation. UNSURE@MICCAI 2024: 34-44 - [c135]Yun Xing, Qing Guo, Xiaofeng Cao, Ivor W. Tsang, Lei Ma:
MetaRepair: Learning to Repair Deep Neural Networks from Repairing Experiences. ACM Multimedia 2024: 1781-1790 - [c134]Cheng Chen, Bowen Xing, Ivor W. Tsang:
Low-Hanging Fruit: Knowledge Distillation from Noisy Teachers for Open Domain Spoken Language Understanding. ECML/PKDD (4) 2024: 107-125 - 2023
- [c133]Haotian Wu, Bowen Xing, Ivor W. Tsang:
MTKDN: Multi-Task Knowledge Disentanglement Network for Recommendation. CIKM 2023: 4360-4364 - [c132]Jiachang Liu, Qi Zhang, Chongyang Shi, Usman Naseem, Shoujin Wang, Liang Hu, Ivor W. Tsang:
Causal Intervention for Abstractive Related Work Generation. EMNLP (Findings) 2023: 2148-2159 - [c131]Xiaoguang Li, Qing Guo, Rabab Abdelfattah, Di Lin, Wei Feng, Ivor W. Tsang, Song Wang:
Leveraging Inpainting for Single-Image Shadow Removal. ICCV 2023: 13009-13018 - [c130]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Iterative Machine Teaching. ICML 2023: 40851-40870 - [c129]Feiyang Ye, Xuehao Wang, Yu Zhang, Ivor W. Tsang:
Multi-Task Learning via Time-Aware Neural ODE. IJCAI 2023: 4495-4503 - [c128]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Teaching for Multiple Learners. NeurIPS 2023 - [c127]Bowen Xing, Ivor W. Tsang:
Co-Evolving Graph Reasoning Network for Emotion-Cause Pair Extraction. ECML/PKDD (1) 2023: 305-322 - 2022
- [c126]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv, Quanhui Liu:
Multi-View Clustering on Topological Manifold. AAAI 2022: 6944-6951 - [c125]Bowen Xing, Ivor W. Tsang:
DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition. ACL (Findings) 2022: 3611-3621 - [c124]Bowen Xing, Ivor W. Tsang:
Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphs. EMNLP 2022: 159-169 - [c123]Bowen Xing, Ivor W. Tsang:
Group is better than individual: Exploiting Label Topologies and Label Relations for Joint Multiple Intent Detection and Slot Filling. EMNLP 2022: 3964-3975 - [c122]Yan Zhang, Changyu Li, Ivor W. Tsang, Hui Xu, Lixin Duan, Hongzhi Yin, Wen Li, Jie Shao:
Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations. ICDE 2022: 2942-2955 - [c121]Bowen Xing, Ivor W. Tsang:
Neural Subgraph Explorer: Reducing Noisy Information via Target-oriented Syntax Graph Pruning. IJCAI 2022: 4425-4431 - [c120]Shudong Huang, Yixi Liu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Learning Smooth Representation for Multi-view Subspace Clustering. ACM Multimedia 2022: 3421-3429 - [c119]Shudong Huang, Hongjie Wu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu, Wentao Feng, Jiancheng Lv:
Multi-view Subspace Clustering on Topological Manifold. NeurIPS 2022 - [c118]Xiaowei Zhou, Jie Yin, Ivor W. Tsang:
Edge but not Least: Cross-View Graph Pooling. ECML/PKDD (2) 2022: 344-359 - 2021
- [c117]Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting. KDD 2021: 269-278 - [c116]Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv, Quanhui Liu:
CDD: Multi-view Subspace Clustering via Cross-view Diversity Detection. ACM Multimedia 2021: 2308-2316 - [c115]Xiaowei Zhou, Jie Yin, Ivor W. Tsang, Chen Wang:
Human-Understandable Decision Making for Visual Recognition. PAKDD (3) 2021: 168-180 - [c114]Yueming Lyu, Ivor W. Tsang:
Black-Box Optimizer with Stochastic Implicit Natural Gradient. ECML/PKDD (3) 2021: 217-232 - 2020
- [c113]Yanxin Zhang, Guanping Xiao, Zheng Zheng, Tianqing Zhu, Ivor W. Tsang, Yulei Sui:
An Empirical Study of Code Deobfuscations on Detecting Obfuscated Android Piggybacked Apps. APSEC 2020: 41-50 - [c112]Yang Zhang, Ivor W. Tsang, Yawei Luo, Chang-Hui Hu, Xiaobo Lu, Xin Yu:
Copy and Paste GAN: Face Hallucination From Shaded Thumbnails. CVPR 2020: 7353-7362 - [c111]Mingjie Li, Ying Zhang, Yifang Sun, Wei Wang, Ivor W. Tsang, Xuemin Lin:
I/O Efficient Approximate Nearest Neighbour Search based on Learned Functions. ICDE 2020: 289-300 - [c110]Yueming Lyu, Ivor W. Tsang:
Curriculum Loss: Robust Learning and Generalization against Label Corruption. ICLR 2020 - [c109]Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama:
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. ICML 2020: 4006-4016 - [c108]Xingrui Yu, Yueming Lyu, Ivor W. Tsang:
Intrinsic Reward Driven Imitation Learning via Generative Model. ICML 2020: 10925-10935 - [c107]Maosen Li, Siheng Chen, Ya Zhang, Ivor W. Tsang:
Graph Cross Networks with Vertex Infomax Pooling. NeurIPS 2020 - [c106]Yueming Lyu, Yuan Yuan, Ivor W. Tsang:
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo. NeurIPS 2020 - 2019
- [c105]Yaxin Shi, Donna Xu, Yuangang Pan, Ivor W. Tsang, Shirui Pan:
Label Embedding with Partial Heterogeneous Contexts. AAAI 2019: 4926-4933 - [c104]Huangjie Zheng, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Jia Wang:
Understanding VAEs in Fisher-Shannon Plane. AAAI 2019: 5917-5924 - [c103]Jiangchao Yao, Hao Wu, Ya Zhang, Ivor W. Tsang, Jun Sun:
Safeguarded Dynamic Label Regression for Noisy Supervision. AAAI 2019: 9103-9110 - [c102]Man Wu, Shirui Pan, Lan Du, Ivor W. Tsang, Xingquan Zhu, Bo Du:
Long-short Distance Aggregation Networks for Positive Unlabeled Graph Learning. CIKM 2019: 2157-2160 - [c101]Yuan Yuan, Yueming Lyu, Xi Shen, Ivor W. Tsang, Dit-Yan Yeung:
Marginalized Average Attentional Network for Weakly-Supervised Learning. ICLR (Poster) 2019 - [c100]Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang, Masashi Sugiyama:
How does Disagreement Help Generalization against Label Corruption? ICML 2019: 7164-7173 - [c99]Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao:
Support Matching: A Novel Regularization to Escape from Mode Collapse in GANs. ICONIP (4) 2019: 40-48 - [c98]Xiaofeng Xu, Ivor W. Tsang, Xiaofeng Cao, Ruiheng Zhang, Chuancai Liu:
Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation. IJCAI 2019: 3989-3995 - [c97]Tao Zheng, Wei-Jie Chen, Ivor W. Tsang, Xin Yao:
Rectified Encoder Network for High-Dimensional Imbalanced Learning. PRICAI (2) 2019: 684-697 - 2018
- [c96]Weiwei Liu, Zhuanghua Liu, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin:
Doubly Approximate Nearest Neighbor Classification. AAAI 2018: 3683-3690 - [c95]Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong:
Compact Multi-Label Learning. AAAI 2018: 4066-4073 - [c94]Joey Tianyi Zhou, Kai Di, Jiawei Du, Xi Peng, Hao Yang, Sinno Jialin Pan, Ivor W. Tsang, Yong Liu, Zheng Qin, Rick Siow Mong Goh:
SC2Net: Sparse LSTMs for Sparse Coding. AAAI 2018: 4588-4595 - [c93]Mingjie Li, Ying Zhang, Yifang Sun, Wei Wang, Ivor W. Tsang, Xuemin Lin:
An Efficient Exact Nearest Neighbor Search by Compounded Embedding. DASFAA (1) 2018: 37-54 - [c92]Xiaobo Shen, Weiwei Liu, Yong Luo, Yew-Soon Ong, Ivor W. Tsang:
Deep Discrete Prototype Multilabel Learning. IJCAI 2018: 2675-2681 - [c91]Chunyang Liu, Ling Chen, Ivor W. Tsang, Hongzhi Yin:
Towards the Learning of Weighted Multi-label Associative Classifiers. IJCNN 2018: 1-7 - [c90]Defu Lian, Kai Zheng, Vincent W. Zheng, Yong Ge, Longbing Cao, Ivor W. Tsang, Xing Xie:
High-order Proximity Preserving Information Network Hashing. KDD 2018: 1744-1753 - [c89]Yan Zhang, Haoyu Wang, Defu Lian, Ivor W. Tsang, Hongzhi Yin, Guowu Yang:
Discrete Ranking-based Matrix Factorization with Self-Paced Learning. KDD 2018: 2758-2767 - [c88]Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor W. Tsang, Ya Zhang, Masashi Sugiyama:
Masking: A New Perspective of Noisy Supervision. NeurIPS 2018: 5841-5851 - [c87]Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama:
Co-teaching: Robust training of deep neural networks with extremely noisy labels. NeurIPS 2018: 8536-8546 - 2017
- [c86]Zhuanghua Liu, Ivor W. Tsang:
Approximate Conditional Gradient Descent on Multi-Class Classification. AAAI 2017: 2301-2307 - [c85]Xiao-Bo Shen, Weiwei Liu, Ivor W. Tsang, Fumin Shen, Quan-Sen Sun:
Compressed K-Means for Large-Scale Clustering. AAAI 2017: 2527-2533 - [c84]Li Wang, Qi Mao, Ivor W. Tsang:
Latent Smooth Skeleton Embedding. AAAI 2017: 2703-2709 - [c83]Jing Chai, Weiwei Liu, Ivor W. Tsang, Xiao-Bo Shen:
Compact Multiple-Instance Learning. CIKM 2017: 2007-2010 - [c82]Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Jun Sun:
Discovering User Interests from Social Images. MMM (2) 2017: 160-172 - [c81]Weiwei Liu, Xiao-Bo Shen, Ivor W. Tsang:
Sparse Embedded k-Means Clustering. NIPS 2017: 3319-3327 - 2016
- [c80]Weiwei Liu, Ivor W. Tsang:
Sparse Perceptron Decision Tree for Millions of Dimensions. AAAI 2016: 1881-1887 - [c79]Mingkui Tan, Yan Yan, Li Wang, Anton van den Hengel, Ivor W. Tsang, Qinfeng (Javen) Shi:
Learning Sparse Confidence-Weighted Classifier on Very High Dimensional Data. AAAI 2016: 2080-2086 - [c78]Jim Jing-Yan Wang, Ivor Wai-Hung Tsang, Xin Gao:
Optimizing Multivariate Performance Measures from Multi-View Data. AAAI 2016: 2152-2158 - [c77]Yan Yan, Zhongwen Xu, Ivor W. Tsang, Guodong Long, Yi Yang:
Robust Semi-Supervised Learning through Label Aggregation. AAAI 2016: 2244-2250 - [c76]Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang, Shen-Shyang Ho:
Transfer Learning for Cross-Language Text Categorization through Active Correspondences Construction. AAAI 2016: 2400-2406 - [c75]Qin Zhang, Jia Wu, Peng Zhang, Guodong Long, Ivor W. Tsang, Chengqi Zhang:
Inferring Latent Network from Cascade Data for Dynamic Social Recommendation. ICDM 2016: 669-678 - [c74]Joey Tianyi Zhou, Xinxing Xu, Sinno Jialin Pan, Ivor W. Tsang, Zheng Qin, Rick Siow Mong Goh:
Transfer Hashing with Privileged Information. IJCAI 2016: 2414-2420 - [c73]Bo Han, Ivor W. Tsang, Ling Chen:
On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent. ECML/PKDD (1) 2016: 665-680 - 2015
- [c72]Weiwei Liu, Zhi-Hong Deng, Xiuwen Gong, Frank Jiang, Ivor W. Tsang:
Effectively Predicting Whether and When a Topic Will Become Prevalent in a Social Network. AAAI 2015: 210-216 - [c71]Weiwei Liu, Ivor W. Tsang:
Large Margin Metric Learning for Multi-Label Prediction. AAAI 2015: 2800-2806 - [c70]Haishuai Wang, Peng Zhang, Ivor W. Tsang, Ling Chen, Chengqi Zhang:
Defragging Subgraph Features for Graph Classification. CIKM 2015: 1687-1690 - [c69]Marcus Chen, Santiago Velasco-Forero, Ivor W. Tsang, Tat-Jen Cham:
Objects co-segmentation: Propagated from simpler images. ICASSP 2015: 1682-1686 - [c68]Yan Yan, Mingkui Tan, Ivor W. Tsang, Yi Yang, Chengqi Zhang, Qinfeng Shi:
Scalable Maximum Margin Matrix Factorization by Active Riemannian Subspace Search. IJCAI 2015: 3988-3994 - [c67]Weiwei Liu, Ivor W. Tsang:
On the Optimality of Classifier Chain for Multi-label Classification. NIPS 2015: 712-720 - 2014
- [c66]Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang, Yan Yan:
Hybrid Heterogeneous Transfer Learning through Deep Learning. AAAI 2014: 2213-2220 - [c65]Sharath Chandra Guntuku, Joey Tianyi Zhou, Sujoy Roy, Weisi Lin, Ivor W. Tsang:
Deep Representations to Model User 'Likes'. ACCV (1) 2014: 3-18 - [c64]Minh Luan Nguyen, Ivor W. Tsang, Kian Ming Adam Chai, Hai Leong Chieu:
Robust Domain Adaptation for Relation Extraction via Clustering Consistency. ACL (1) 2014: 807-817 - [c63]Joey Tianyi Zhou, Ivor W. Tsang, Sinno Jialin Pan, Mingkui Tan:
Heterogeneous Domain Adaptation for Multiple Classes. AISTATS 2014: 1095-1103 - [c62]Zhongwen Xu, Ivor W. Tsang, Yi Yang, Zhigang Ma, Alexander G. Hauptmann:
Event Detection Using Multi-level Relevance Labels and Multiple Features. CVPR 2014: 97-104 - [c61]Ping Liu, Joey Tianyi Zhou, Ivor Wai-Hung Tsang, Zibo Meng, Shizhong Han, Yan Tong:
Feature Disentangling Machine - A Novel Approach of Feature Selection and Disentangling in Facial Expression Analysis. ECCV (4) 2014: 151-166 - [c60]Mingkui Tan, Ivor W. Tsang, Li Wang, Bart Vandereycken, Sinno Jialin Pan:
Riemannian Pursuit for Big Matrix Recovery. ICML 2014: 1539-1547 - 2013
- [c59]Zhongwen Xu, Yi Yang, Ivor W. Tsang, Nicu Sebe, Alexander G. Hauptmann:
Feature Weighting via Optimal Thresholding for Video Analysis. ICCV 2013: 3440-3447 - 2012
- [c58]Mingkui Tan, Ivor W. Tsang, Li Wang, Xinming Zhang:
Convex Matching Pursuit for Large-Scale Sparse Coding and Subset Selection. AAAI 2012: 1119-1125 - [c57]Lin Chen, Lixin Duan, Ivor W. Tsang, Dong Xu:
Efficient Discriminative Learning of Class Hierarchy for Many Class Prediction. ACCV (1) 2012: 274-288 - [c56]Liang Feng, Yew-Soon Ong, Ivor Wai-Hung Tsang, Ah-Hwee Tan:
An evolutionary search paradigm that learns with past experiences. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c55]Chun-Wei Seah, Yew-Soon Ong, Ivor W. Tsang, Siwei Jiang:
Pareto Rank Learning in Multi-objective Evolutionary Algorithms. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c54]Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu:
Batch mode Adaptive Multiple Instance Learning for computer vision tasks. CVPR 2012: 2368-2375 - [c53]Jian-Bo Yang, Qi Mao, Qiaoliang Xiang, Ivor Wai-Hung Tsang, Kian Ming Adam Chai, Hai Leong Chieu:
Domain Adaptation for Coreference Resolution: An Adaptive Ensemble Approach. EMNLP-CoNLL 2012: 744-753 - [c52]Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu:
Co-labeling: A New Multi-view Learning Approach for Ambiguous Problems. ICDM 2012: 419-428 - [c51]Xinxing Xu, Ivor W. Tsang, Dong Xu:
Handling Ambiguity via Input-Output Kernel Learning. ICDM 2012: 725-734 - [c50]Chun-Wei Seah, Ivor Wai-Hung Tsang, Yew-Soon Ong, Qi Mao:
Learning Target Predictive Function without Target Labels. ICDM 2012: 1098-1103 - [c49]Lixin Duan, Dong Xu, Ivor W. Tsang:
Learning with Augmented Features for Heterogeneous Domain Adaptation. ICML 2012 - [c48]Qiaoliang Xiang, Qi Mao, Kian Ming Adam Chai, Hai Leong Chieu, Ivor W. Tsang, Zhendong Zhao:
A Split-Merge Framework for Comparing Clusterings. ICML 2012 - [c47]Yiteng Zhai, Mingkui Tan, Ivor W. Tsang, Yew-Soon Ong:
Discovering Support and Affiliated Features from Very High Dimensions. ICML 2012 - [c46]Joey Tianyi Zhou, Sinno Jialin Pan, Qi Mao, Ivor W. Tsang:
Multi-view Positive and Unlabeled Learning. ACML 2012: 555-570 - 2011
- [c45]Shenghua Gao, Liang-Tien Chia, Ivor Wai-Hung Tsang:
Multi-layer group sparse coding - For concurrent image classification and annotation. CVPR 2011: 2809-2816 - [c44]Wen Li, Lixin Duan, Dong Xu, Ivor Wai-Hung Tsang:
Text-based image retrieval using progressive multi-instance learning. ICCV 2011: 2049-2055 - [c43]Chun-Wei Seah, Ivor Wai-Hung Tsang, Yew-Soon Ong:
Healing Sample Selection Bias by Source Classifier Selection. ICDM 2011: 577-586 - [c42]Qi Mao, Ivor Wai-Hung Tsang:
Optimizing Performance Measures for Feature Selection. ICDM 2011: 1170-1175 - [c41]Shukai Li, Ivor W. Tsang, Narendra S. Chaudhari:
Infinite Decision Agent Ensemble Learning System for Credit Risk Analysis. ICMLA (1) 2011: 36-39 - [c40]Shukai Li, Ivor W. Tsang:
Maximum Margin/Volume Outlier Detection. ICTAI 2011: 385-392 - [c39]Jian-Bo Yang, Ivor W. Tsang:
Hierarchical Maximum Margin Learning for Multi-Class Classification. UAI 2011: 753-760 - [c38]Shukai Li, Ivor W. Tsang:
Learning to Locate Relative Outliers. ACML 2011: 47-62 - [c37]Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi:
Two-Layer Multiple Kernel Learning. AISTATS 2011: 909-917 - 2010
- [c36]William-Chandra Tjhi, Gary Kee Khoon Lee, Terence Hung, Yew-Soon Ong, Ivor Wai-Hung Tsang, Victor Racine, Frédéric Bard:
Clustering-based methodology with minimal user supervision for displaying cell-phenotype signatures in image-based screening. BIBM Workshops 2010: 252-257 - [c35]Lixin Duan, Dong Xu, Ivor Wai-Hung Tsang, Jiebo Luo:
Visual event recognition in videos by learning from web data. CVPR 2010: 1959-1966 - [c34]Lin Chen, Dong Xu, Ivor Wai-Hung Tsang, Jiebo Luo:
Tag-based web photo retrieval improved by batch mode re-tagging. CVPR 2010: 3440-3446 - [c33]Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia, Peilin Zhao:
Local features are not lonely - Laplacian sparse coding for image classification. CVPR 2010: 3555-3561 - [c32]Shenghua Gao, Ivor Wai-Hung Tsang, Liang-Tien Chia:
Kernel Sparse Representation for Image Classification and Face Recognition. ECCV (4) 2010: 1-14 - [c31]Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
Location and Scatter Matching for Dataset Shift in Text Mining. ICDM 2010: 773-778 - [c30]Mingkui Tan, Li Wang, Ivor W. Tsang:
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets. ICML 2010: 1047-1054 - [c29]Shenghua Gao, Zhengxiang Wang, Liang-Tien Chia, Ivor Wai-Hung Tsang:
Automatic image tagging via category label and web data. ACM Multimedia 2010: 1115-1118 - [c28]Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong, Gary Kee Khoon Lee:
Predictive Distribution Matching SVM for Multi-domain Learning. ECML/PKDD (1) 2010: 231-247 - [c27]Qi Mao, Ivor W. Tsang:
Parameter-Free Spectral Kernel Learning. UAI 2010: 350-357 - 2009
- [c26]Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu, Stephen J. Maybank:
Domain Transfer SVM for video concept detection. CVPR 2009: 1375-1381 - [c25]Lixin Duan, Ivor W. Tsang, Dong Xu, Tat-Seng Chua:
Domain adaptation from multiple sources via auxiliary classifiers. ICML 2009: 289-296 - [c24]Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi:
SimpleNPKL: simple non-parametric kernel learning. ICML 2009: 1273-1280 - [c23]Feiping Nie, Dong Xu, Ivor W. Tsang, Changshui Zhang:
Spectral Embedded Clustering. IJCAI 2009: 1181-1186 - [c22]Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qiang Yang:
Domain Adaptation via Transfer Component Analysis. IJCAI 2009: 1187-1192 - [c21]Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
Extracting discriminative concepts for domain adaptation in text mining. KDD 2009: 179-188 - [c20]Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo:
Using large-scale web data to facilitate textual query based retrieval of consumer photos. ACM Multimedia 2009: 55-64 - [c19]Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo:
T-IRS: textual query based image retrieval system for consumer photos. ACM Multimedia 2009: 983-984 - [c18]Yufeng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua Zhou:
A Convex Method for Locating Regions of Interest with Multi-instance Learning. ECML/PKDD (2) 2009: 15-30 - [c17]Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
A Semi-Supervised Framework for Feature Mapping and Multiclass Classification. SDM 2009: 341-352 - [c16]Yufeng Li, Ivor W. Tsang, James Tin-Yau Kwok, Zhi-Hua Zhou:
Tighter and Convex Maximum Margin Clustering. AISTATS 2009: 344-351 - 2008
- [c15]Kai Zhang, Ivor W. Tsang, James T. Kwok:
Improved Nyström low-rank approximation and error analysis. ICML 2008: 1232-1239 - 2007
- [c14]Ivor W. Tsang, András Kocsor, James T. Kwok:
Simpler core vector machines with enclosing balls. ICML 2007: 911-918 - [c13]Kai Zhang, Ivor W. Tsang, James T. Kwok:
Maximum margin clustering made practical. ICML 2007: 1119-1126 - [c12]Ivor W. Tsang, James T. Kwok:
Ensembles of Partially Trained SVMs with Multiplicative Updates. IJCAI 2007: 1089-1094 - 2006
- [c11]Ivor W. Tsang, András Kocsor, James T. Kwok:
Diversified SVM Ensembles for Large Data Sets. ECML 2006: 792-800 - [c10]Ivor W. Tsang, James T. Kwok, Brian Mak, Kai Zhang, Jeffrey Junfeng Pan:
Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression. ICASSP (1) 2006: 997-1000 - [c9]Ivor W. Tsang, James T. Kwok, Shutao Li:
Learning the Kernel in Mahalanobis One-Class Support Vector Machines. IJCNN 2006: 1169-1175 - [c8]Ivor W. Tsang, András Kocsor, James T. Kwok:
Efficient kernel feature extraction for massive data sets. KDD 2006: 724-729 - [c7]Ivor W. Tsang, James T. Kwok:
Large-Scale Sparsified Manifold Regularization. NIPS 2006: 1401-1408 - 2005
- [c6]Ivor W. Tsang, James Tin-Yau Kwok, Pak-Ming Cheung:
Very Large SVM Training using Core Vector Machines. AISTATS 2005: 349-356 - [c5]Kin Fung Simon Wong, Ivor W. Tsang, Victor Cheung, S.-H. Gary Chan, James T. Kwok:
Position estimation for wireless sensor networks. GLOBECOM 2005: 5 - [c4]Ivor W. Tsang, James T. Kwok, Kimo T. Lai:
Core Vector Regression for very large regression problems. ICML 2005: 912-919 - 2004
- [c3]Ivor W. Tsang, James T. Kwok:
Efficient Hyperkernel Learning Using Second-Order Cone Programming. ECML 2004: 453-464 - 2003
- [c2]James T. Kwok, Ivor W. Tsang:
Learning with Idealized Kernels. ICML 2003: 400-407 - [c1]James T. Kwok, Ivor W. Tsang:
The Pre-Image Problem in Kernel Methods. ICML 2003: 408-415
Editorship
- 2022
- [e2]Vineeth N. Balasubramanian, Ivor W. Tsang:
Asian Conference on Machine Learning, ACML 2022, 12-14 December 2022, Hyderabad, India. Proceedings of Machine Learning Research 189, PMLR 2022 [contents] - 2021
- [e1]Vineeth N. Balasubramanian, Ivor W. Tsang:
Asian Conference on Machine Learning, ACML 2021, 17-19 November 2021, Virtual Event. Proceedings of Machine Learning Research 157, PMLR 2021 [contents]
Informal and Other Publications
- 2024
- [i128]Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang:
A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. CoRR abs/2401.09257 (2024) - [i127]Jinliang Deng, Xuan Song, Ivor W. Tsang, Hui Xiong:
The Bigger the Better? Rethinking the Effective Model Scale in Long-term Time Series Forecasting. CoRR abs/2401.11929 (2024) - [i126]Bohao Qu, Xiaofeng Cao, Qing Guo, Yi Chang, Ivor W. Tsang, Chengqi Zhang:
Transductive Reward Inference on Graph. CoRR abs/2402.03661 (2024) - [i125]Yanjun Zhao, Sizhe Dang, Haishan Ye, Guang Dai, Yi Qian, Ivor W. Tsang:
Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer. CoRR abs/2402.15173 (2024) - [i124]Yang He, Lingao Xiao, Joey Tianyi Zhou, Ivor W. Tsang:
Multisize Dataset Condensation. CoRR abs/2403.06075 (2024) - [i123]Sensen Gao, Xiaojun Jia, Xuhong Ren, Ivor W. Tsang, Qing Guo:
Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial Trajectory. CoRR abs/2403.12445 (2024) - [i122]Ming Yan, Joey Tianyi Zhou, Ivor W. Tsang:
Collaborative Knowledge Infusion for Low-resource Stance Detection. CoRR abs/2403.19219 (2024) - [i121]Bowen Xing, Ivor W. Tsang:
HC2L: Hybrid and Cooperative Contrastive Learning for Cross-lingual Spoken Language Understanding. CoRR abs/2405.06204 (2024) - [i120]Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai, Ivor W. Tsang:
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient. CoRR abs/2405.17761 (2024) - [i119]Xiaoting Lyu, Yufei Han, Wei Wang, Hangwei Qian, Ivor W. Tsang, Xiangliang Zhang:
Cross-Context Backdoor Attacks against Graph Prompt Learning. CoRR abs/2405.17984 (2024) - [i118]Yueming Lyu, Kim Yong Tan, Yew Soon Ong, Ivor W. Tsang:
Covariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generation. CoRR abs/2406.00812 (2024) - [i117]Feng Hong, Yueming Lyu, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Yanfeng Wang:
Diversified Batch Selection for Training Acceleration. CoRR abs/2406.04872 (2024) - [i116]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
PROUD: PaRetO-gUided Diffusion Model for Multi-objective Generation. CoRR abs/2407.04493 (2024) - [i115]Zhenglin Wan, Xingrui Yu, David Mark Bossens, Yueming Lyu, Qing Guo, Flint Xiaofeng Fan, Ivor W. Tsang:
Quality Diversity Imitation Learning. CoRR abs/2410.06151 (2024) - [i114]Han Ling, Yinghui Sun, Quansen Sun, Ivor W. Tsang, Yuhui Zheng:
Self-Assessed Generation: Trustworthy Label Generation for Optical Flow and Stereo Matching in Real-world. CoRR abs/2410.10453 (2024) - [i113]Feiyang Ye, Yueming Lyu, Xuehao Wang, Masashi Sugiyama, Yu Zhang, Ivor W. Tsang:
Sharpness-Aware Black-Box Optimization. CoRR abs/2410.12457 (2024) - [i112]Xin He, Shunkang Zhang, Yuxin Wang, Haiyan Yin, Zihao Zeng, Shaohuai Shi, Zhenheng Tang, Xiaowen Chu, Ivor W. Tsang, Yew-Soon Ong:
ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference. CoRR abs/2410.17954 (2024) - [i111]Zongyi Xiang, Yan Zhang, Lixin Duan, Hongzhi Yin, Ivor W. Tsang:
Coherence-guided Preference Disentanglement for Cross-domain Recommendations. CoRR abs/2410.20580 (2024) - 2023
- [i110]Yuhao Liu, Qing Guo, Lan Fu, Zhanghan Ke, Ke Xu, Wei Feng, Ivor W. Tsang, Rynson W. H. Lau:
Structure-Informed Shadow Removal Networks. CoRR abs/2301.03182 (2023) - [i109]Xiaoguang Li, Qing Guo, Rabab Abdelfattah, Di Lin, Wei Feng, Ivor W. Tsang, Song Wang:
Leveraging Inpainting for Single-Image Shadow Removal. CoRR abs/2302.05361 (2023) - [i108]Jiangchao Yao, Bo Han, Zhihan Zhou, Ya Zhang, Ivor W. Tsang:
Latent Class-Conditional Noise Model. CoRR abs/2302.09595 (2023) - [i107]Cheng Chen, Yueming Lyu, Ivor W. Tsang:
Adversary-Aware Partial label learning with Label distillation. CoRR abs/2304.00498 (2023) - [i106]Kim Yong Tan, Yueming Lyu, Yew Soon Ong, Ivor W. Tsang:
Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search. CoRR abs/2304.02350 (2023) - [i105]Yaxin Shi, Xiaowei Zhou, Ping Liu, Ivor W. Tsang:
UTSGAN: Unseen Transition Suss GAN for Transition-Aware Image-to-image Translation. CoRR abs/2304.11955 (2023) - [i104]Jing Li, Yuangang Pan, Yueming Lyu, Yinghua Yao, Yulei Sui, Ivor W. Tsang:
Earning Extra Performance from Restrictive Feedbacks. CoRR abs/2304.14831 (2023) - [i103]Xiaoguang Li, Qing Guo, Pingping Cai, Wei Feng, Ivor W. Tsang, Song Wang:
Learning Restoration is Not Enough: Transfering Identical Mapping for Single-Image Shadow Removal. CoRR abs/2305.10640 (2023) - [i102]Jinliang Deng, Xiusi Chen, Renhe Jiang, Du Yin, Yi Yang, Xuan Song, Ivor W. Tsang:
Learning Structured Components: Towards Modular and Interpretable Multivariate Time Series Forecasting. CoRR abs/2305.13036 (2023) - [i101]Jiachang Liu, Qi Zhang, Chongyang Shi, Usman Naseem, Shoujin Wang, Ivor W. Tsang:
Causal Intervention for Abstractive Related Work Generation. CoRR abs/2305.13685 (2023) - [i100]Yihao Huang, Yue Cao, Tianlin Li, Felix Juefei-Xu, Di Lin, Ivor W. Tsang, Yang Liu, Qing Guo:
On the Robustness of Segment Anything. CoRR abs/2305.16220 (2023) - [i99]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Iterative Machine Teaching. CoRR abs/2306.03007 (2023) - [i98]Bowen Xing, Ivor W. Tsang:
Co-evolving Graph Reasoning Network for Emotion-Cause Pair Extraction. CoRR abs/2306.04340 (2023) - [i97]Bowen Xing, Ivor W. Tsang:
Relational Temporal Graph Reasoning for Dual-task Dialogue Language Understanding. CoRR abs/2306.09114 (2023) - [i96]Canyu Zhang, Qing Guo, Xiaoguang Li, Renjie Wan, Hongkai Yu, Ivor W. Tsang, Song Wang:
SuperInpaint: Learning Detail-Enhanced Attentional Implicit Representation for Super-resolutional Image Inpainting. CoRR abs/2307.14489 (2023) - [i95]Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor W. Tsang, Yong Liu:
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold. CoRR abs/2308.10547 (2023) - [i94]Kairui Hu, Ming Yan, Joey Tianyi Zhou, Ivor W. Tsang, Wen Haw Chong, Yong Keong Yap:
Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection. CoRR abs/2308.16763 (2023) - [i93]Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang, Yang Liu, Qing Guo:
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks. CoRR abs/2310.11890 (2023) - [i92]Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
Sanitized Clustering against Confounding Bias. CoRR abs/2311.01252 (2023) - [i91]Mingwei Xu, Xiaofeng Cao, Ivor W. Tsang, James T. Kwok:
Aggregation Weighting of Federated Learning via Generalization Bound Estimation. CoRR abs/2311.05936 (2023) - [i90]Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok:
Nonparametric Teaching for Multiple Learners. CoRR abs/2311.10318 (2023) - [i89]Bowen Xing, Ivor W. Tsang:
Co-guiding for Multi-intent Spoken Language Understanding. CoRR abs/2312.03716 (2023) - [i88]Bowen Xing, Ivor W. Tsang:
Exploiting Contextual Target Attributes for Target Sentiment Classification. CoRR abs/2312.13766 (2023) - [i87]Tuan-Anh Vu, Duc Thanh Nguyen, Qing Guo, Binh-Son Hua, Nhat Minh Chung, Ivor W. Tsang, Sai-Kit Yeung:
Leveraging Open-Vocabulary Diffusion to Camouflaged Instance Segmentation. CoRR abs/2312.17505 (2023) - 2022
- [i86]Bowen Xing, Ivor W. Tsang:
DigNet: Digging Clues from Local-Global Interactive Graph for Aspect-level Sentiment Classification. CoRR abs/2201.00989 (2022) - [i85]Bowen Xing, Ivor W. Tsang:
DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition. CoRR abs/2203.03856 (2022) - [i84]Yan Zhang, Changyu Li, Ivor W. Tsang, Hui Xu, Lixin Duan, Hongzhi Yin, Wen Li, Jie Shao:
Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations. CoRR abs/2204.00327 (2022) - [i83]Bowen Xing, Ivor W. Tsang:
Neural Subgraph Explorer: Reducing Noisy Information via Target-Oriented Syntax Graph Pruning. CoRR abs/2205.10970 (2022) - [i82]Xiaowei Zhou, Ivor W. Tsang, Jie Yin:
Latent Boundary-guided Adversarial Training. CoRR abs/2206.03717 (2022) - [i81]Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang:
Data-Efficient Learning via Minimizing Hyperspherical Energy. CoRR abs/2206.15204 (2022) - [i80]Xiaofeng Cao, Yaming Guo, Tieru Wu, Ivor W. Tsang:
When an Active Learner Meets a Black-box Teacher. CoRR abs/2206.15205 (2022) - [i79]Xiaofeng Cao, Weixin Bu, Shengjun Huang, Ying-Peng Tang, Yaming Guo, Yi Chang, Ivor W. Tsang:
A Survey of Learning on Small Data. CoRR abs/2207.14443 (2022) - [i78]Bowen Xing, Ivor W. Tsang:
Group is better than individual: Exploiting Label Topologies and Label Relations for Joint Multiple Intent Detection and Slot Filling. CoRR abs/2210.10369 (2022) - [i77]Bowen Xing, Ivor W. Tsang:
Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphs. CoRR abs/2210.10375 (2022) - [i76]Chen Zhang, Xiaofeng Cao, Yi Chang, Ivor W. Tsang:
One-shot Machine Teaching: Cost Very Few Examples to Converge Faster. CoRR abs/2212.06416 (2022) - [i75]Peiyao Zhao, Yuangang Pan, Xin Li, Xu Chen, Ivor W. Tsang, Lejian Liao:
Coarse-to-Fine Contrastive Learning on Graphs. CoRR abs/2212.06423 (2022) - 2021
- [i74]Xiaowei Zhou, Jie Yin, Ivor W. Tsang, Chen Wang:
Human-Understandable Decision Making for Visual Recognition. CoRR abs/2103.03429 (2021) - [i73]Yaxin Shi, Xiaowei Zhou, Ping Liu, Ivor W. Tsang:
Generative Transition Mechanism to Image-to-Image Translation via Encoded Transformation. CoRR abs/2103.05193 (2021) - [i72]Xiaofeng Cao, Ivor W. Tsang:
Bayesian Active Learning by Disagreements: A Geometric Perspective. CoRR abs/2105.02543 (2021) - [i71]Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya Zhang, Hao Zhang, Ivor W. Tsang, Jingren Zhou, Mingyuan Zhou:
Contrastive Conditional Transport for Representation Learning. CoRR abs/2105.03746 (2021) - [i70]Xiaofeng Cao, Ivor W. Tsang:
Distribution Matching for Machine Teaching. CoRR abs/2105.13809 (2021) - [i69]Yueming Lyu, Ivor W. Tsang:
Neural Optimization Kernel: Towards Robust Deep Learning. CoRR abs/2106.06097 (2021) - [i68]Bowen Xing, Ivor W. Tsang:
Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis. CoRR abs/2106.10816 (2021) - [i67]Boyuan Zheng, Sunny Verma, Jianlong Zhou, Ivor W. Tsang, Fang Chen:
Imitation Learning: Progress, Taxonomies and Opportunities. CoRR abs/2106.12177 (2021) - [i66]Maosen Li, Siheng Chen, Yanning Shen, Genjia Liu, Ivor W. Tsang, Ya Zhang:
Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network. CoRR abs/2107.00894 (2021) - [i65]Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao:
Differential-Critic GAN: Generating What You Want by a Cue of Preferences. CoRR abs/2107.06700 (2021) - [i64]Bowen Xing, Ivor W. Tsang:
Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Network. CoRR abs/2108.02352 (2021) - [i63]Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang:
A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecasting. CoRR abs/2109.01657 (2021) - [i62]Xiaowei Zhou, Jie Yin, Ivor W. Tsang:
Edge but not Least: Cross-View Graph Pooling. CoRR abs/2109.11796 (2021) - [i61]Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao:
TRIP: Refining Image-to-Image Translation via Rival Preferences. CoRR abs/2111.13411 (2021) - [i60]Jing Li, Yuangang Pan, Ivor W. Tsang:
Taming Overconfident Prediction on Unlabeled Data from Hindsight. CoRR abs/2112.08200 (2021) - 2020
- [i59]Zhuanghua Liu, Ivor W. Tsang:
Towards Sharper First-Order Adversary with Quantized Gradients. CoRR abs/2002.02372 (2020) - [i58]Yang Zhang, Ivor W. Tsang, Jun Li, Ping Liu, Xiaobo Lu, Xin Yu:
Face Hallucination with Finishing Touches. CoRR abs/2002.03308 (2020) - [i57]Yang Zhang, Ivor W. Tsang, Yawei Luo, Changhui Hu, Xiaobo Lu, Xin Yu:
Copy and Paste GAN: Face Hallucination from Shaded Thumbnails. CoRR abs/2002.10650 (2020) - [i56]Jing Li, Yuangang Pan, Yulei Sui, Ivor W. Tsang:
Secure Metric Learning via Differential Pairwise Privacy. CoRR abs/2003.13413 (2020) - [i55]Yaxin Shi, Yuangang Pan, Donna Xu, Ivor W. Tsang:
Multi-view Alignment and Generation in CCA via Consistent Latent Encoding. CoRR abs/2005.11716 (2020) - [i54]Xingrui Yu, Yueming Lyu, Ivor W. Tsang:
Intrinsic Reward Driven Imitation Learning via Generative Model. CoRR abs/2006.15061 (2020) - [i53]Xu Chen, Ya Zhang, Ivor W. Tsang, Yuangang Pan:
Learning Robust Node Representations on Graphs. CoRR abs/2008.11416 (2020) - [i52]Xu Chen, Ya Zhang, Ivor W. Tsang, Yuangang Pan, Jingchao Su:
Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation. CoRR abs/2009.06884 (2020) - [i51]Hao Zhang, Joey Tianyi Zhou, Tianying Wang, Ivor W. Tsang, Rick Siow Mong Goh:
Deep N-ary Error Correcting Output Codes. CoRR abs/2009.10465 (2020) - [i50]Maosen Li, Siheng Chen, Ya Zhang, Ivor W. Tsang:
Graph Cross Networks with Vertex Infomax Pooling. CoRR abs/2010.01804 (2020) - [i49]Yan Zhang, Ivor W. Tsang, Hongzhi Yin, Guowu Yang, Defu Lian, Jingjing Li:
Deep Pairwise Hashing for Cold-start Recommendation. CoRR abs/2011.00944 (2020) - [i48]Yan Zhang, Ivor W. Tsang, Lixin Duan:
Collaborative Generative Hashing for Marketing and Fast Cold-start Recommendation. CoRR abs/2011.00953 (2020) - [i47]Xu Chen, Siheng Chen, Jiangchao Yao, Huangjie Zheng, Ya Zhang, Ivor W. Tsang:
Learning on Attribute-Missing Graphs. CoRR abs/2011.01623 (2020) - [i46]Bo Han, Quanming Yao, Tongliang Liu, Gang Niu, Ivor W. Tsang, James T. Kwok, Masashi Sugiyama:
A Survey of Label-noise Representation Learning: Past, Present and Future. CoRR abs/2011.04406 (2020) - [i45]Yueming Lyu, Yuan Yuan, Ivor W. Tsang:
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo. CoRR abs/2011.06446 (2020) - [i44]Weiwei Liu, Xiaobo Shen, Haobo Wang, Ivor W. Tsang:
The Emerging Trends of Multi-Label Learning. CoRR abs/2011.11197 (2020) - 2019
- [i43]Donna Xu, Yaxin Shi, Ivor W. Tsang, Yew-Soon Ong, Chen Gong, Xiaobo Shen:
A Survey on Multi-output Learning. CoRR abs/1901.00248 (2019) - [i42]Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang, Masashi Sugiyama:
How does Disagreement Help Generalization against Label Corruption? CoRR abs/1901.04215 (2019) - [i41]Xiaofeng Xu, Ivor W. Tsang, Xiaofeng Cao, Ruiheng Zhang, Chuancai Liu:
Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation. CoRR abs/1905.07933 (2019) - [i40]Yuan Yuan, Yueming Lyu, Xi Shen, Ivor W. Tsang, Dit-Yan Yeung:
Marginalized Average Attentional Network for Weakly-Supervised Learning. CoRR abs/1905.08586 (2019) - [i39]Yueming Lyu, Yuan Yuan, Ivor W. Tsang:
Efficient Batch Black-box Optimization with Deterministic Regret Bounds. CoRR abs/1905.10041 (2019) - [i38]Yueming Lyu, Ivor W. Tsang:
Curriculum Loss: Robust Learning and Generalization against Label Corruption. CoRR abs/1905.10045 (2019) - [i37]Yuangang Pan, Weijie Chen, Gang Niu, Ivor W. Tsang, Masashi Sugiyama:
Fast and Robust Rank Aggregation against Model Misspecification. CoRR abs/1905.12341 (2019) - [i36]Yaxin Shi, Yuangang Pan, Donna Xu, Ivor W. Tsang:
Probabilistic CCA with Implicit Distributions. CoRR abs/1907.02345 (2019) - [i35]Xiaowei Zhou, Ivor W. Tsang, Jie Yin:
Latent Adversarial Defence with Boundary-guided Generation. CoRR abs/1907.07001 (2019) - [i34]Xu Chen, Siheng Chen, Huangjie Zheng, Jiangchao Yao, Kenan Cui, Ya Zhang, Ivor W. Tsang:
Node Attribute Generation on Graphs. CoRR abs/1907.09708 (2019) - [i33]Xiaofeng Xu, Ivor W. Tsang, Chuancai Liu:
Improving Generalization via Attribute Selection on Out-of-the-box Data. CoRR abs/1907.11397 (2019) - [i32]Huiting Hong, Xin Li, Yuangang Pan, Ivor W. Tsang:
Domain-adversarial Network Alignment. CoRR abs/1908.05429 (2019) - [i31]Yueming Lyu, Ivor W. Tsang:
Stochastic Implicit Natural Gradient for Black-box Optimization. CoRR abs/1910.04301 (2019) - 2018
- [i30]Huangjie Zheng, Jiangchao Yao, Ya Zhang, Ivor W. Tsang:
Degeneration in VAE: in the Light of Fisher Information Loss. CoRR abs/1802.06677 (2018) - [i29]Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama:
Millionaire: A Hint-guided Approach for Crowdsourcing. CoRR abs/1802.09172 (2018) - [i28]Fanhua Shang, Kaiwen Zhou, James Cheng, Ivor W. Tsang, Lijun Zhang, Dacheng Tao:
VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. CoRR abs/1802.09932 (2018) - [i27]Jiangchao Yao, Ivor W. Tsang, Ya Zhang:
Variational Composite Autoencoders. CoRR abs/1804.04435 (2018) - [i26]Xiaofeng Xu, Ivor W. Tsang, Chuancai Liu:
Zero-shot Learning with Complementary Attributes. CoRR abs/1804.06505 (2018) - [i25]Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang, Masashi Sugiyama:
Co-sampling: Training Robust Networks for Extremely Noisy Supervision. CoRR abs/1804.06872 (2018) - [i24]Yaxin Shi, Donna Xu, Yuangang Pan, Ivor W. Tsang:
Multi-Context Label Embedding. CoRR abs/1805.01199 (2018) - [i23]Bo Han, Jiangchao Yao, Gang Niu, Mingyuan Zhou, Ivor W. Tsang, Ya Zhang, Masashi Sugiyama:
Masking: A New Perspective of Noisy Supervision. CoRR abs/1805.08193 (2018) - [i22]Miao Xu, Gang Niu, Bo Han, Ivor W. Tsang, Zhi-Hua Zhou, Masashi Sugiyama:
Matrix Co-completion for Multi-label Classification with Missing Features and Labels. CoRR abs/1805.09156 (2018) - [i21]Huangjie Zheng, Jiangchao Yao, Ya Zhang, Ivor W. Tsang:
Understanding VAEs in Fisher-Shannon Plane. CoRR abs/1807.03723 (2018) - [i20]Bo Han, Gang Niu, Jiangchao Yao, Xingrui Yu, Miao Xu, Ivor W. Tsang, Masashi Sugiyama:
Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels. CoRR abs/1809.11008 (2018) - [i19]Bo Han, Ivor W. Tsang, Xiaokui Xiao, Ling Chen, Sai-Fu Fung, Celina Ping Yu:
Privacy-preserving Stochastic Gradual Learning. CoRR abs/1810.00383 (2018) - 2017
- [i18]Jiangchao Yao, Jiajie Wang, Ivor W. Tsang, Ya Zhang, Jun Sun, Chengqi Zhang, Rui Zhang:
Deep Learning from Noisy Image Labels with Quality Embedding. CoRR abs/1711.00583 (2017) - [i17]Donna Xu, Ivor W. Tsang, Ying Zhang:
Online Product Quantization. CoRR abs/1711.10775 (2017) - 2016
- [i16]Joey Tianyi Zhou, Ivor W. Tsang, Shen-Shyang Ho, Klaus-Robert Müller:
N-ary Error Correcting Coding Scheme. CoRR abs/1603.05850 (2016) - [i15]Xinxing Xu, Joey Tianyi Zhou, Ivor W. Tsang, Zheng Qin, Rick Siow Mong Goh, Yong Liu:
Simple and Efficient Learning using Privileged Information. CoRR abs/1604.01518 (2016) - [i14]Bo Han, Ivor W. Tsang, Ling Chen:
On the Convergence of A Family of Robust Losses for Stochastic Gradient Descent. CoRR abs/1605.01623 (2016) - [i13]Joey Tianyi Zhou, Xinxing Xu, Sinno Jialin Pan, Ivor W. Tsang, Zheng Qin, Rick Siow Mong Goh:
Transfer Hashing with Privileged Information. CoRR abs/1605.04034 (2016) - 2015
- [i12]Qi Mao, Li Wang, Ivor W. Tsang, Yijun Sun:
A Novel Regularized Principal Graph Learning Framework on Explicit Graph Representation. CoRR abs/1512.02752 (2015) - 2013
- [i11]Mingkui Tan, Ivor W. Tsang, Li Wang:
Is Matching Pursuit Solving Convex Problems? CoRR abs/1302.5010 (2013) - [i10]Yufeng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou:
Convex and Scalable Weakly Labeled SVMs. CoRR abs/1303.1271 (2013) - 2012
- [i9]Jian-Bo Yang, Ivor W. Tsang:
Hierarchical Maximum Margin Learning for Multi-Class Classification. CoRR abs/1202.3770 (2012) - [i8]Qi Mao, Ivor W. Tsang:
Parameter-Free Spectral Kernel Learning. CoRR abs/1203.3495 (2012) - [i7]Lixin Duan, Dong Xu, Ivor W. Tsang:
Learning with Augmented Features for Heterogeneous Domain Adaptation. CoRR abs/1206.4660 (2012) - [i6]Liang Feng, Yew-Soon Ong, Ah-Hwee Tan, Ivor Wai-Hung Tsang:
Meme as Building Block for Evolutionary Optimization of Problem Instances. CoRR abs/1207.0702 (2012) - [i5]Mingkui Tan, Ivor W. Tsang, Li Wang:
Towards Large-scale and Ultrahigh Dimensional Feature Selection via Feature Generation. CoRR abs/1209.5260 (2012) - 2011
- [i4]Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong:
Transductive Ordinal Regression. CoRR abs/1102.2808 (2011) - [i3]Qi Mao, Ivor W. Tsang:
Multiple Template Learning for Structured Prediction. CoRR abs/1103.0890 (2011) - [i2]Qi Mao, Ivor W. Tsang:
A Feature Selection Method for Multivariate Performance Measures. CoRR abs/1103.1013 (2011) - 2010
- [i1]Nan Li, Ivor W. Tsang, Zhi-Hua Zhou:
Efficiently Learning Nonlinear Classifiers for Domain Specific Performance Measures. CoRR abs/1012.0930 (2010)
Coauthor Index
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