Tsang, Ivor W.

100 publications

ICCV 2025 Balanced Image Stylization with Style Matching Score Yuxin Jiang, Liming Jiang, Shuai Yang, Jia-Wei Liu, Ivor W. Tsang, Mike Zheng Shou

IJCAI 2025 Grounding Open-Domain Knowledge from LLMs to Real-World Reinforcement Learning Tasks: A Survey Haiyan Yin, Hangwei Qian, Yaxin Shi, Ivor W. Tsang, Yew-Soon Ong

MLJ 2025 Group Feature Selection Using Non-Class Data Chunna Li, Yuangang Pan, Weijie Chen, Ivor W. Tsang, Yuanhai Shao

IJCAI 2025 Instructing Text-to-Image Diffusion Models via Classifier-Guided Semantic Optimization Yuanyuan Chang, Yinghua Yao, Tao Qin, Mengmeng Wang, Ivor W. Tsang, Guang Dai

AAAI 2025 Max-Mahalanobis Anchors Guidance for Multi-View Clustering Pei Zhang, Yuangang Pan, Siwei Wang, Shengju Yu, Huiying Xu, En Zhu, Xinwang Liu, Ivor W. Tsang

MLJ 2025 Sandbox: Safeguarded Multi-Label Learning Through Safe Optimal Transport Lefei Zhang, Geng Yu, Jiangchao Yao, Yew-Soon Ong, Ivor W. Tsang, James T. Kwok

MLJ 2025 Uncover and Unlearn Nuisances: Agnostic Fully Test-Time Adaptation Ponhvoan Srey, Yaxin Shi, Hangwei Qian, Jing Li, Ivor W. Tsang

CVPR 2024 AHIVE: Anatomy-Aware Hierarchical Vision Encoding for Interactive Radiology Report Retrieval Sixing Yan, William K. Cheung, Ivor W. Tsang, Keith Chiu, Terence M. Tong, Ka Chun Cheung, Simon See

JAIR 2024 Exploiting Contextual Target Attributes for Target Sentiment Classification Bowen Xing, Ivor W. Tsang

IJCAI 2024 Fast Unpaired Multi-View Clustering Xingfeng Li, Yuangang Pan, Yinghui Sun, Quansen Sun, Ivor W. Tsang, Zhenwen Ren

JMLR 2024 Generative Adversarial Ranking Nets Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao

JMLR 2024 Learning Discretized Neural Networks Under Ricci Flow Jun Chen, Hanwen Chen, Mengmeng Wang, Guang Dai, Ivor W. Tsang, Yong Liu

ECML-PKDD 2024 Low-Hanging Fruit: Knowledge Distillation from Noisy Teachers for Open Domain Spoken Language Understanding Cheng Chen, Bowen Xing, Ivor W. Tsang

JMLR 2024 Mentored Learning: Improving Generalization and Convergence of Student Learner Xiaofeng Cao, Yaming Guo, Heng Tao Shen, Ivor W. Tsang, James T. Kwok

MLJ 2024 PROUD: PaRetO-gUided Diffusion Model for Multi-Objective Generation Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao

MLJ 2024 Sanitized Clustering Against Confounding Bias Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao

NeurIPS 2024 Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization Mingwei Xu, Xiaofeng Cao, Ivor W. Tsang

NeurIPS 2024 Towards Harmless Rawlsian Fairness Regardless of Demographic Prior Xuanqian Wang, Jing Li, Ivor W. Tsang, Yew-Soon Ong

JAIR 2024 USN: A Robust Imitation Learning Method Against Diverse Action Noise Xingrui Yu, Bo Han, Ivor W. Tsang

ECML-PKDD 2023 Co-Evolving Graph Reasoning Network for Emotion-Cause Pair Extraction Bowen Xing, Ivor W. Tsang

MLJ 2023 LADDER: Latent Boundary-Guided Adversarial Training Xiaowei Zhou, Ivor W. Tsang, Jie Yin

IJCAI 2023 Multi-Task Learning via Time-Aware Neural ODE Feiyang Ye, Xuehao Wang, Yu Zhang, Ivor W. Tsang

NeurIPS 2023 Nonparametric Teaching for Multiple Learners Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok

ECML-PKDD 2022 Edge but Not Least: Cross-View Graph Pooling Xiaowei Zhou, Jie Yin, Ivor W. Tsang

JMLR 2022 Fast and Robust Rank Aggregation Against Model Misspecification Yuangang Pan, Ivor W. Tsang, Weijie Chen, Gang Niu, Masashi Sugiyama

AAAI 2022 Multi-View Clustering on Topological Manifold Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv, Quanhui Liu

NeurIPS 2022 Multi-View Subspace Clustering on Topological Manifold Shudong Huang, Hongjie Wu, Yazhou Ren, Ivor W. Tsang, Zenglin Xu, Wentao Feng, Jiancheng Lv

MLJ 2022 Multiple Partitions Alignment via Spectral Rotation Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv

IJCAI 2022 Neural Subgraph Explorer: Reducing Noisy Information via Target-Oriented Syntax Graph Pruning Bowen Xing, Ivor W. Tsang

JAIR 2022 Out of Context: A New Clue for Context Modeling of Aspect-Based Sentiment Analysis Bowen Xing, Ivor W. Tsang

JMLR 2022 XAI Beyond Classification: Interpretable Neural Clustering Xi Peng, Yunfan Li, Ivor W. Tsang, Hongyuan Zhu, Jiancheng Lv, Joey Tianyi Zhou

ECML-PKDD 2021 Black-Box Optimizer with Stochastic Implicit Natural Gradient Yueming Lyu, Ivor W. Tsang

ICLR 2020 Collaborative Generated Hashing for Market Analysis and Fast Cold-Start Recommendation Yan Zhang, Ivor W. Tsang, Lixin Duan, Guowu Yang

ICLR 2020 Curriculum Loss: Robust Learning and Generalization Against Label Corruption Yueming Lyu, Ivor W. Tsang

NeurIPS 2020 Graph Cross Networks with Vertex Infomax Pooling Maosen Li, Siheng Chen, Ya Zhang, Ivor W. Tsang

NeurIPS 2020 Subgroup-Based Rank-1 Lattice Quasi-Monte Carlo Yueming Lyu, Yuan Yuan, Ivor W. Tsang

AAAI 2019 Label Embedding with Partial Heterogeneous Contexts Yaxin Shi, Donna Xu, Yuangang Pan, Ivor W. Tsang, Shirui Pan

IJCAI 2019 Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation Xiaofeng Xu, Ivor W. Tsang, Xiaofeng Cao, Ruiheng Zhang, Chuancai Liu

ICLR 2019 Marginalized Average Attentional Network for Weakly-Supervised Learning Yuan Yuan, Yueming Lyu, Xi Shen, Ivor W. Tsang, Dit-Yan Yeung

MLJ 2019 Millionaire: A Hint-Guided Approach for Crowdsourcing Bo Han, Quanming Yao, Yuangang Pan, Ivor W. Tsang, Xiaokui Xiao, Qiang Yang, Masashi Sugiyama

JMLR 2019 Multi-Class Heterogeneous Domain Adaptation Joey Tianyi Zhou, Ivor W. Tsang, Sinno Jialin Pan, Mingkui Tan

MLJ 2019 N-Ary Decomposition for Multi-Class Classification Joey Tianyi Zhou, Ivor W. Tsang, Shen-Shyang Ho, Klaus-Robert Müller

AAAI 2019 Safeguarded Dynamic Label Regression for Noisy Supervision Jiangchao Yao, Hao Wu, Ya Zhang, Ivor W. Tsang, Jun Sun

AAAI 2019 Understanding VAEs in Fisher-Shannon Plane Huangjie Zheng, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Jia Wang

AAAI 2018 Compact Multi-Label Learning Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong

IJCAI 2018 Deep Discrete Prototype Multilabel Learning Xiaobo Shen, Weiwei Liu, Yong Luo, Yew-Soon Ong, Ivor W. Tsang

AAAI 2018 Doubly Approximate Nearest Neighbor Classification Weiwei Liu, Zhuanghua Liu, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin

MLJ 2018 Robust Plackett-Luce Model for K-Ary Crowdsourced Preferences Bo Han, Yuangang Pan, Ivor W. Tsang

AAAI 2018 SC2Net: Sparse LSTMs for Sparse Coding 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

MLJ 2018 Stagewise Learning for Noisy K-Ary Preferences Yuangang Pan, Bo Han, Ivor W. Tsang

MLJ 2017 A Unified Probabilistic Framework for Robust Manifold Learning and Embedding Qi Mao, Li Wang, Ivor W. Tsang

JMLR 2017 An Easy-to-Hard Learning Paradigm for Multiple Classes and Multiple Labels Weiwei Liu, Ivor W. Tsang, Klaus-Robert Müller

AAAI 2017 Approximate Conditional Gradient Descent on Multi-Class Classification Zhuanghua Liu, Ivor W. Tsang

AAAI 2017 Compressed K-Means for Large-Scale Clustering Xiao-Bo Shen, Weiwei Liu, Ivor W. Tsang, Fumin Shen, Quan-Sen Sun

AAAI 2017 Latent Smooth Skeleton Embedding Li Wang, Qi Mao, Ivor W. Tsang

JMLR 2017 Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions Weiwei Liu, Ivor W. Tsang

AAAI 2016 Learning Sparse Confidence-Weighted Classifier on Very High Dimensional Data Mingkui Tan, Yan Yan, Li Wang, Anton van den Hengel, Ivor W. Tsang, Qinfeng (Javen) Shi

ECML-PKDD 2016 On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent Bo Han, Ivor W. Tsang, Ling Chen

AAAI 2016 Robust Semi-Supervised Learning Through Label Aggregation Yan Yan, Zhongwen Xu, Ivor W. Tsang, Guodong Long, Yi Yang

AAAI 2016 Sparse Perceptron Decision Tree for Millions of Dimensions Weiwei Liu, Ivor W. Tsang

IJCAI 2016 Transfer Hashing with Privileged Information Joey Tianyi Zhou, Xinxing Xu, Sinno Jialin Pan, Ivor W. Tsang, Zheng Qin, Rick Siow Mong Goh

AAAI 2016 Transfer Learning for Cross-Language Text Categorization Through Active Correspondences Construction Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang, Shen-Shyang Ho

AAAI 2015 Effectively Predicting Whether and When a Topic Will Become Prevalent in a Social Network Weiwei Liu, Zhi-Hong Deng, Xiuwen Gong, Frank Jiang, Ivor W. Tsang

AAAI 2015 Large Margin Metric Learning for Multi-Label Prediction Weiwei Liu, Ivor W. Tsang

IJCAI 2015 Scalable Maximum Margin Matrix Factorization by Active Riemannian Subspace Search Yan Yan, Mingkui Tan, Ivor W. Tsang, Yi Yang, Chengqi Zhang, Qinfeng Shi

CVPR 2014 Event Detection Using Multi-Level Relevance Labels and Multiple Features Zhongwen Xu, Ivor W. Tsang, Yi Yang, Zhigang Ma, Alexander G. Hauptmann

AISTATS 2014 Heterogeneous Domain Adaptation for Multiple Classes Joey Tianyi Zhou, Ivor W. Tsang, Sinno Jialin Pan, Mingkui Tan

AAAI 2014 Hybrid Heterogeneous Transfer Learning Through Deep Learning Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang, Yan Yan

ICML 2014 Riemannian Pursuit for Big Matrix Recovery Mingkui Tan, Ivor W. Tsang, Li Wang, Bart Vandereycken, Sinno Jialin Pan

JMLR 2014 Towards Ultrahigh Dimensional Feature Selection for Big Data Mingkui Tan, Ivor W. Tsang, Li Wang

JMLR 2013 Convex and Scalable Weakly Labeled SVMs Yu-Feng Li, Ivor W. Tsang, James T. Kwok, Zhi-Hua Zhou

ICML 2012 A Split-Merge Framework for Comparing Clusterings Qiaoliang Xiang, Qi Mao, Kian Ming Adam Chai, Hai Leong Chieu, Ivor W. Tsang, Zhendong Zhao

AAAI 2012 Convex Matching Pursuit for Large-Scale Sparse Coding and Subset Selection Mingkui Tan, Ivor W. Tsang, Li Wang, Xinming Zhang

ICML 2012 Discovering Support and Affiliated Features from Very High Dimensions Yiteng Zhai, Mingkui Tan, Ivor W. Tsang, Yew-Soon Ong

ICML 2012 Learning with Augmented Features for Heterogeneous Domain Adaptation Lixin Duan, Dong Xu, Ivor W. Tsang

ACML 2012 Multi-View Positive and Unlabeled Learning Joey Tianyi Zhou, Sinno Jialin Pan, Qi Mao, Ivor W. Tsang

JMLR 2011 A Family of Simple Non-Parametric Kernel Learning Algorithms Jinfeng Zhuang, Ivor W. Tsang, Steven C.H. Hoi

UAI 2011 Hierarchical Maximum Margin Learning for Multi-Class Classification Jian-Bo Yang, Ivor W. Tsang

ACML 2011 Learning to Locate Relative Outliers Shukai Li, Ivor W. Tsang

AISTATS 2011 Two-Layer Multiple Kernel Learning Jinfeng Zhuang, Ivor W. Tsang, Steven C.H. Hoi

ICML 2010 Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets Mingkui Tan, Li Wang, Ivor W. Tsang

UAI 2010 Parameter-Free Spectral Kernel Learning Qi Mao, Ivor W. Tsang

ECML-PKDD 2010 Predictive Distribution Matching SVM for Multi-Domain Learning Chun-Wei Seah, Ivor W. Tsang, Yew-Soon Ong, Gary Kee Khoon Lee

ECML-PKDD 2009 A Convex Method for Locating Regions of Interest with Multi-Instance Learning Yufeng Li, James T. Kwok, Ivor W. Tsang, Zhi-Hua Zhou

ICML 2009 Domain Adaptation from Multiple Sources via Auxiliary Classifiers Lixin Duan, Ivor W. Tsang, Dong Xu, Tat-Seng Chua

IJCAI 2009 Domain Adaptation via Transfer Component Analysis Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qiang Yang

ICML 2009 SimpleNPKL: Simple Non-Parametric Kernel Learning Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi

IJCAI 2009 Spectral Embedded Clustering Feiping Nie, Dong Xu, Ivor W. Tsang, Changshui Zhang

AISTATS 2009 Tighter and Convex Maximum Margin Clustering Yu-Feng Li, Ivor W. Tsang, Jame Kwok, Zhi-Hua Zhou

ICML 2008 Improved Nyström Low-Rank Approximation and Error Analysis Kai Zhang, Ivor W. Tsang, James T. Kwok

IJCAI 2007 Ensembles of Partially Trained SVMs with Multiplicative Updates Ivor W. Tsang, James T. Kwok

ICML 2007 Maximum Margin Clustering Made Practical Kai Zhang, Ivor W. Tsang, James T. Kwok

ICML 2007 Simpler Core Vector Machines with Enclosing Balls Ivor W. Tsang, András Kocsor, James T. Kwok

ECML-PKDD 2006 Diversified SVM Ensembles for Large Data Sets Ivor W. Tsang, András Kocsor, James T. Kwok

NeurIPS 2006 Large-Scale Sparsified Manifold Regularization Ivor W. Tsang, James T. Kwok

JMLR 2005 Core Vector Machines: Fast SVM Training on Very Large Data Sets Ivor W. Tsang, James T. Kwok, Pak-Ming Cheung

ICML 2005 Core Vector Regression for Very Large Regression Problems Ivor W. Tsang, James T. Kwok, Kimo T. Lai

ECML-PKDD 2004 Efficient Hyperkernel Learning Using Second-Order Cone Programming Ivor W. Tsang, James T. Kwok

ICML 2003 Learning with Idealized Kernels James T. Kwok, Ivor W. Tsang

ICML 2003 The Pre-Image Problem in Kernel Methods James T. Kwok, Ivor W. Tsang