| 2026 | AAAI | Correspondence Coverage Matters for Multi-Modal Dataset Distillation. | Zhuohang Dang, Minnan Luo, Chengyou Jia, Hangwei Qian, Xinyu Zhang, Xiaojun Chang, Ivor W. Tsang |
| 2026 | AAAI | GenMatLab: A Generative Platform for Inverse Materials Design. | Hangwei Qian, Yang He, Yaxin Shi, Ivor W. Tsang |
| 2026 | AAAI | MAGIC: Mastering Physical Adversarial Generation in Context Through Collaborative LLM Agents. | Yun Xing, Nhat Chung, Jie Zhang, Yue Cao, Ivor W. Tsang, Yang Liu, Lei Ma, Qing Guo |
| 2026 | ACL | From Language to Driving: A Dual-Loop SLM-Enhanced Framework for Multi-Planner Scheduling via a Domain-Specific Language. | Jiawei Liu, Xun Gong, Muli Yang, Xingrui Yu, Fen Fang, Xulei Yang, Ivor W. Tsang, Yunfeng Hu, Hong Chen, Qing Guo |
| 2026 | ACL | Safety Sidecar: Reflection-Driven Runtime Control for Safer Agents. | Bin Wang, Jiazheng Quan, Xingrui Yu, Hansen Hu, Yu Hao, Anjun Gao, Zhenglin Wan, Hui Li, Ivor W. Tsang |
| 2026 | ICDE | JetBGC: Joint Robust Embedding and Structural Fusion Bipartite Graph Clustering (Extended Abstract). | Liang Li, Yuangang Pan, Junpu Zhang, Pei Zhang, Jie Liu, Xinwang Liu, Kenli Li, Ivor W. Tsang, Keqin Li |
| 2026 | WACV | Power of Boundary and Reflection: Semantic Transparent Object Segmentation using Pyramid Vision Transformer with Transparent Cues. | Tuan-Anh Vu, Hai Nguyen-Truong, Ziqiang Zheng, Binh-Son Hua, Qing Guo, Ivor W. Tsang, Sai-Kit Yeung |
| 2025 | AAAI | 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 |
| 2025 | CVPR | SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments. | Yue Cao, Yun Xing, Jie Zhang, Di Lin, Tianwei Zhang, Ivor W. Tsang, Yang Liu, Qing Guo |
| 2025 | ECAI | HynetImpute: Missing Pattern Specialized Imputation via Hypernetwork. | Ken Cheong, William K. Cheung, Ivor W. Tsang |
| 2025 | ICCV | Balanced Image Stylization with Style Matching Score. | Yuxin Jiang, Liming Jiang, Shuai Yang, Jia-Wei Liu, Ivor W. Tsang, Mike Zheng Shou |
| 2025 | ICDE | Boosting with Fewer Tokens: Multi-Query Optimization for LLMs Using Node Text and Neighbor Cues. | Yujie Fang, Xin Li, Yuangang Pan, Xin Huang, Ivor W. Tsang |
| 2025 | ICDE | BGAE: Auto-encoding Multi-view Bipartite Graph Clustering (Extended Abstract). | Liang Li, Yuangang Pan, Jie Liu, Yue Liu, Xinwang Liu, Kenli Li, Ivor W. Tsang, Keqin Li |
| 2025 | ICLR | Sharpness-Aware Black-Box Optimization. | Feiyang Ye, Yueming Lyu, Xuehao Wang, Masashi Sugiyama, Yu Zhang, Ivor W. Tsang |
| 2025 | ICLR | Training-Free Dataset Pruning for Instance Segmentation. | Yalun Dai, Lingao Xiao, Ivor W. Tsang, Yang He |
| 2025 | ICLR | ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs. | Hao Di, Tong He, Haishan Ye, Yinghui Huang, Xiangyu Chang, Guang Dai, Ivor W. Tsang |
| 2025 | ICLR | Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation. | Kim Yong Tan, Yueming Lyu, Ivor W. Tsang, Yew-Soon Ong |
| 2025 | ICLR | Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer. | Yanjun Zhao, Sizhe Dang, Haishan Ye, Guang Dai, Yi Qian, Ivor W. Tsang |
| 2025 | ICLR | Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration. | Heyang Zhao, Xingrui Yu, David Mark Bossens, Ivor W. Tsang, Quanquan Gu |
| 2025 | ICML | Analytical Construction on Geometric Architectures: Transitioning from Static to Temporal Link Prediction. | Yadong Sun, Xiaofeng Cao, Ivor W. Tsang, Heng Tao Shen |
| 2025 | ICML | Diversifying Policy Behaviors with Extrinsic Behavioral Curiosity. | Zhenglin Wan, Xingrui Yu, David Mark Bossens, Yueming Lyu, Qing Guo, Flint Xiaofeng Fan, Yew-Soon Ong, Ivor W. Tsang |
| 2025 | IJCAI | Instructing Text-to-Image Diffusion Models via Classifier-Guided Semantic Optimization. | Yuanyuan Chang, Yinghua Yao, Tao Qin, Mengmeng Wang, Ivor W. Tsang, Guang Dai |
| 2025 | IJCAI | 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 |
| 2024 | CVPR | AHIVE: Anatomy-Aware Hierarchical Vision Encoding for Interactive Radiology Report Retrieval. | Sixing Yan, William K. Cheung, Ivor W. Tsang, Wan Hang Keith Chiu, Terence M. Tong, Ka Chun Cheung, Simon See |
| 2024 | ECAI | A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. | Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, Ivor W. Tsang |
| 2024 | ECCV | Boosting Transferability in Vision-Language Attacks via Diversification Along the Intersection Region of Adversarial Trajectory. | Sensen Gao, Xiaojun Jia, Xuhong Ren, Ivor W. Tsang, Qing Guo |
| 2024 | EMNLP | DC-Instruct: An Effective Framework for Generative Multi-intent Spoken Language Understanding. | Bowen Xing, Lizi Liao, Minlie Huang, Ivor W. Tsang |
| 2024 | ICLR | Multisize Dataset Condensation. | Yang He, Lingao Xiao, Joey Tianyi Zhou, Ivor W. Tsang |
| 2024 | ICLR | On Harmonizing Implicit Subpopulations. | Feng Hong, Jiangchao Yao, Yueming Lyu, Zhihan Zhou, Ivor W. Tsang, Ya Zhang, Yanfeng Wang |
| 2024 | ICLR | Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold. | Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor W. Tsang, Yong Liu |
| 2024 | ICLR | IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks. | Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor W. Tsang, Yang Liu, Qing Guo |
| 2024 | ICLR | Self-Teaching Prompting for Multi-Intent Learning with Limited Supervision. | Cheng Chen, Ivor W. Tsang |
| 2024 | ICLR | Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning. | Feiyang Ye, Yueming Lyu, Xuehao Wang, Yu Zhang, Ivor W. Tsang |
| 2024 | ICML | Diversified Batch Selection for Training Acceleration. | Feng Hong, Yueming Lyu, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Yanfeng Wang |
| 2024 | ICML | Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods. | Hao Di, Haishan Ye, Xiangyu Chang, Guang Dai, Ivor W. Tsang |
| 2024 | ICML | Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient. | Hao Di, Haishan Ye, Yueling Zhang, Xiangyu Chang, Guang Dai, Ivor W. Tsang |
| 2024 | ICML | Can Gaussian Sketching Converge Faster on a Preconditioned Landscape? | Yilong Wang, Haishan Ye, Guang Dai, Ivor W. Tsang |
| 2024 | IJCAI | Fast Unpaired Multi-view Clustering. | Xingfeng Li, Yuangang Pan, Yinghui Sun, Quansen Sun, Ivor W. Tsang, Zhenwen Ren |
| 2024 | IJCNN | Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection. | Kairui Hu, Ming Yan, Wen Haw Chong, Yong Keong Yap, Cuntai Guan, Joey Tianyi Zhou, Ivor W. Tsang |
| 2024 | KDD | Cross-Context Backdoor Attacks against Graph Prompt Learning. | Xiaoting Lyu, Yufei Han, Wei Wang, Hangwei Qian, Ivor W. Tsang, Xiangliang Zhang |
| 2024 | MICCAI | Diagnose with Uncertainty Awareness: Diagnostic Uncertainty Encoding Framework for Radiology Report Generation. | Sixing Yan, Haiyan Yin, Ivor W. Tsang, William K. Cheung |
| 2023 | CIKM | MTKDN: Multi-Task Knowledge Disentanglement Network for Recommendation. | Haotian Wu, Bowen Xing, Ivor W. Tsang |
| 2023 | EMNLP | Causal Intervention for Abstractive Related Work Generation. | Jiachang Liu, Qi Zhang, Chongyang Shi, Usman Naseem, Shoujin Wang, Liang Hu, Ivor W. Tsang |
| 2023 | ICCV | Leveraging Inpainting for Single-Image Shadow Removal. | Xiaoguang Li, Qing Guo, Rabab Abdelfattah, Di Lin, Wei Feng, Ivor W. Tsang, Song Wang |
| 2023 | ICML | Nonparametric Iterative Machine Teaching. | Chen Zhang, Xiaofeng Cao, Weiyang Liu, Ivor W. Tsang, James T. Kwok |
| 2023 | IJCAI | Multi-Task Learning via Time-Aware Neural ODE. | Feiyang Ye, Xuehao Wang, Yu Zhang, Ivor W. Tsang |
| 2022 | AAAI | Multi-View Clustering on Topological Manifold. | Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv, Quanhui Liu |
| 2022 | ACL | DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition. | Bowen Xing, Ivor W. Tsang |
| 2022 | EMNLP | Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphs. | Bowen Xing, Ivor W. Tsang |
| 2022 | EMNLP | Group is better than individual: Exploiting Label Topologies and Label Relations for Joint Multiple Intent Detection and Slot Filling. | Bowen Xing, Ivor W. Tsang |
| 2022 | ICDE | Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations. | Yan Zhang, Changyu Li, Ivor W. Tsang, Hui Xu, Lixin Duan, Hongzhi Yin, Wen Li, Jie Shao |
| 2022 | IJCAI | Neural Subgraph Explorer: Reducing Noisy Information via Target-oriented Syntax Graph Pruning. | Bowen Xing, Ivor W. Tsang |
| 2021 | KDD | ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting. | Jinliang Deng, Xiusi Chen, Renhe Jiang, Xuan Song, Ivor W. Tsang |
| 2021 | PAKDD | Human-Understandable Decision Making for Visual Recognition. | Xiaowei Zhou, Jie Yin, Ivor W. Tsang, Chen Wang |
| 2020 | APSEC | An Empirical Study of Code Deobfuscations on Detecting Obfuscated Android Piggybacked Apps. | Yanxin Zhang, Guanping Xiao, Zheng Zheng, Tianqing Zhu, Ivor W. Tsang, Yulei Sui |
| 2020 | CVPR | Copy and Paste GAN: Face Hallucination From Shaded Thumbnails. | Yang Zhang, Ivor W. Tsang, Yawei Luo, Chang-Hui Hu, Xiaobo Lu, Xin Yu |
| 2020 | ICDE | I/O Efficient Approximate Nearest Neighbour Search based on Learned Functions. | Mingjie Li, Ying Zhang, Yifang Sun, Wei Wang, Ivor W. Tsang, Xuemin Lin |
| 2020 | ICLR | Curriculum Loss: Robust Learning and Generalization against Label Corruption. | Yueming Lyu, Ivor W. Tsang |
| 2020 | ICML | SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. | Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama |
| 2020 | ICML | Intrinsic Reward Driven Imitation Learning via Generative Model. | Xingrui Yu, Yueming Lyu, Ivor W. Tsang |
| 2019 | AAAI | Label Embedding with Partial Heterogeneous Contexts. | Yaxin Shi, Donna Xu, Yuangang Pan, Ivor W. Tsang, Shirui Pan |
| 2019 | AAAI | Safeguarded Dynamic Label Regression for Noisy Supervision. | Jiangchao Yao, Hao Wu, Ya Zhang, Ivor W. Tsang, Jun Sun |
| 2019 | AAAI | Understanding VAEs in Fisher-Shannon Plane. | Huangjie Zheng, Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Jia Wang |
| 2019 | CIKM | Long-short Distance Aggregation Networks for Positive Unlabeled Graph Learning. | Man Wu, Shirui Pan, Lan Du, Ivor W. Tsang, Xingquan Zhu, Bo Du |
| 2019 | ICLR | Marginalized Average Attentional Network for Weakly-Supervised Learning. | Yuan Yuan, Yueming Lyu, Xi Shen, Ivor W. Tsang, Dit-Yan Yeung |
| 2019 | ICML | How does Disagreement Help Generalization against Label Corruption? | Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang, Masashi Sugiyama |
| 2019 | ICONIP | Support Matching: A Novel Regularization to Escape from Mode Collapse in GANs. | Yinghua Yao, Yuangang Pan, Ivor W. Tsang, Xin Yao |
| 2019 | IJCAI | Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation. | Xiaofeng Xu, Ivor W. Tsang, Xiaofeng Cao, Ruiheng Zhang, Chuancai Liu |
| 2019 | PRICAI | Rectified Encoder Network for High-Dimensional Imbalanced Learning. | Tao Zheng, Wei-Jie Chen, Ivor W. Tsang, Xin Yao |
| 2018 | AAAI | Compact Multi-Label Learning. | Xiaobo Shen, Weiwei Liu, Ivor W. Tsang, Quan-Sen Sun, Yew-Soon Ong |
| 2018 | AAAI | Doubly Approximate Nearest Neighbor Classification. | Weiwei Liu, Zhuanghua Liu, Ivor W. Tsang, Wenjie Zhang, Xuemin Lin |
| 2018 | AAAI | 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 |
| 2018 | DASFAA | An Efficient Exact Nearest Neighbor Search by Compounded Embedding. | Mingjie Li, Ying Zhang, Yifang Sun, Wei Wang, Ivor W. Tsang, Xuemin Lin |
| 2018 | IJCAI | Deep Discrete Prototype Multilabel Learning. | Xiaobo Shen, Weiwei Liu, Yong Luo, Yew-Soon Ong, Ivor W. Tsang |
| 2018 | IJCNN | Towards the Learning of Weighted Multi-label Associative Classifiers. | Chunyang Liu, Ling Chen, Ivor W. Tsang, Hongzhi Yin |
| 2018 | KDD | High-order Proximity Preserving Information Network Hashing. | Defu Lian, Kai Zheng, Vincent W. Zheng, Yong Ge, Longbing Cao, Ivor W. Tsang, Xing Xie |
| 2018 | KDD | Discrete Ranking-based Matrix Factorization with Self-Paced Learning. | Yan Zhang, Haoyu Wang, Defu Lian, Ivor W. Tsang, Hongzhi Yin, Guowu Yang |
| 2017 | AAAI | Approximate Conditional Gradient Descent on Multi-Class Classification. | Zhuanghua Liu, Ivor W. Tsang |
| 2017 | AAAI | Compressed K-Means for Large-Scale Clustering. | Xiao-Bo Shen, Weiwei Liu, Ivor W. Tsang, Fumin Shen, Quan-Sen Sun |
| 2017 | AAAI | Latent Smooth Skeleton Embedding. | Li Wang, Qi Mao, Ivor W. Tsang |
| 2017 | CIKM | Compact Multiple-Instance Learning. | Jing Chai, Weiwei Liu, Ivor W. Tsang, Xiao-Bo Shen |
| 2017 | MMM | Discovering User Interests from Social Images. | Jiangchao Yao, Ya Zhang, Ivor W. Tsang, Jun Sun |
| 2016 | AAAI | Sparse Perceptron Decision Tree for Millions of Dimensions. | Weiwei Liu, Ivor W. Tsang |
| 2016 | AAAI | 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 |
| 2016 | AAAI | Robust Semi-Supervised Learning through Label Aggregation. | Yan Yan, Zhongwen Xu, Ivor W. Tsang, Guodong Long, Yi Yang |
| 2016 | AAAI | Transfer Learning for Cross-Language Text Categorization through Active Correspondences Construction. | Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang, Shen-Shyang Ho |
| 2016 | ICDM | Inferring Latent Network from Cascade Data for Dynamic Social Recommendation. | Qin Zhang, Jia Wu, Peng Zhang, Guodong Long, Ivor W. Tsang, Chengqi Zhang |
| 2016 | IJCAI | Transfer Hashing with Privileged Information. | Joey Tianyi Zhou, Xinxing Xu, Sinno Jialin Pan, Ivor W. Tsang, Zheng Qin, Rick Siow Mong Goh |
| 2015 | AAAI | 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 |
| 2015 | AAAI | Large Margin Metric Learning for Multi-Label Prediction. | Weiwei Liu, Ivor W. Tsang |
| 2015 | CIKM | Defragging Subgraph Features for Graph Classification. | Haishuai Wang, Peng Zhang, Ivor W. Tsang, Ling Chen, Chengqi Zhang |
| 2015 | ICASSP | Objects co-segmentation: Propagated from simpler images. | Marcus Chen, Santiago Velasco-Forero, Ivor W. Tsang, Tat-Jen Cham |
| 2015 | IJCAI | Scalable Maximum Margin Matrix Factorization by Active Riemannian Subspace Search. | Yan Yan, Mingkui Tan, Ivor W. Tsang, Yi Yang, Chengqi Zhang, Qinfeng Shi |
| 2014 | AAAI | Hybrid Heterogeneous Transfer Learning through Deep Learning. | Joey Tianyi Zhou, Sinno Jialin Pan, Ivor W. Tsang, Yan Yan |
| 2014 | ACCV | Deep Representations to Model User 'Likes'. | Sharath Chandra Guntuku, Joey Tianyi Zhou, Sujoy Roy, Weisi Lin, Ivor W. Tsang |
| 2014 | ACL | Robust Domain Adaptation for Relation Extraction via Clustering Consistency. | Minh Luan Nguyen, Ivor W. Tsang, Kian Ming Adam Chai, Hai Leong Chieu |
| 2014 | AISTATS | Heterogeneous Domain Adaptation for Multiple Classes. | Joey Tianyi Zhou, Ivor W. Tsang, Sinno Jialin Pan, Mingkui Tan |
| 2014 | CVPR | Event Detection Using Multi-level Relevance Labels and Multiple Features. | Zhongwen Xu, Ivor W. Tsang, Yi Yang, Zhigang Ma, Alexander G. Hauptmann |
| 2014 | ICML | Riemannian Pursuit for Big Matrix Recovery. | Mingkui Tan, Ivor W. Tsang, Li Wang, Bart Vandereycken, Sinno Jialin Pan |
| 2013 | ICCV | Feature Weighting via Optimal Thresholding for Video Analysis. | Zhongwen Xu, Yi Yang, Ivor W. Tsang, Nicu Sebe, Alexander G. Hauptmann |
| 2012 | AAAI | Convex Matching Pursuit for Large-Scale Sparse Coding and Subset Selection. | Mingkui Tan, Ivor W. Tsang, Li Wang, Xinming Zhang |
| 2012 | ACCV | Efficient Discriminative Learning of Class Hierarchy for Many Class Prediction. | Lin Chen, Lixin Duan, Ivor W. Tsang, Dong Xu |
| 2012 | CEC | Pareto Rank Learning in Multi-objective Evolutionary Algorithms. | Chun-Wei Seah, Yew-Soon Ong, Ivor W. Tsang, Siwei Jiang |
| 2012 | ICDM | Handling Ambiguity via Input-Output Kernel Learning. | Xinxing Xu, Ivor W. Tsang, Dong Xu |
| 2012 | ICML | Learning with Augmented Features for Heterogeneous Domain Adaptation. | Lixin Duan, Dong Xu, Ivor W. Tsang |
| 2012 | ICML | A Split-Merge Framework for Comparing Clusterings. | Qiaoliang Xiang, Qi Mao, Kian Ming Adam Chai, Hai Leong Chieu, Ivor W. Tsang, Zhendong Zhao |
| 2012 | ICML | Discovering Support and Affiliated Features from Very High Dimensions. | Yiteng Zhai, Mingkui Tan, Ivor W. Tsang, Yew-Soon Ong |
| 2011 | ICMLA | Infinite Decision Agent Ensemble Learning System for Credit Risk Analysis. | Shukai Li, Ivor W. Tsang, Narendra S. Chaudhari |
| 2011 | ICTAI | Maximum Margin/Volume Outlier Detection. | Shukai Li, Ivor W. Tsang |
| 2011 | UAI | Hierarchical Maximum Margin Learning for Multi-Class Classification. | Jian-Bo Yang, Ivor W. Tsang |
| 2010 | ICDM | Location and Scatter Matching for Dataset Shift in Text Mining. | Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong |
| 2010 | ICML | Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets. | Mingkui Tan, Li Wang, Ivor W. Tsang |
| 2010 | UAI | Parameter-Free Spectral Kernel Learning. | Qi Mao, Ivor W. Tsang |
| 2009 | ICML | Domain adaptation from multiple sources via auxiliary classifiers. | Lixin Duan, Ivor W. Tsang, Dong Xu, Tat-Seng Chua |
| 2009 | ICML | SimpleNPKL: simple non-parametric kernel learning. | Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi |
| 2009 | IJCAI | Spectral Embedded Clustering. | Feiping Nie, Dong Xu, Ivor W. Tsang, Changshui Zhang |
| 2009 | IJCAI | Domain Adaptation via Transfer Component Analysis. | Sinno Jialin Pan, Ivor W. Tsang, James T. Kwok, Qiang Yang |
| 2009 | KDD | Extracting discriminative concepts for domain adaptation in text mining. | Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong |
| 2009 | SDM | A Semi-Supervised Framework for Feature Mapping and Multiclass Classification. | Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong |
| 2008 | ICML | Improved Nystrm low-rank approximation and error analysis. | Kai Zhang, Ivor W. Tsang, James T. Kwok |
| 2007 | ICML | Simpler core vector machines with enclosing balls. | Ivor W. Tsang, Andrs Kocsor, James T. Kwok |
| 2007 | ICML | Maximum margin clustering made practical. | Kai Zhang, Ivor W. Tsang, James T. Kwok |
| 2007 | IJCAI | Ensembles of Partially Trained SVMs with Multiplicative Updates. | Ivor W. Tsang, James T. Kwok |
| 2006 | ICASSP | Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression. | Ivor W. Tsang, James T. Kwok, Brian Mak, Kai Zhang, Jeffrey Junfeng Pan |
| 2006 | IJCNN | Learning the Kernel in Mahalanobis One-Class Support Vector Machines. | Ivor W. Tsang, James T. Kwok, Shutao Li |
| 2006 | KDD | Efficient kernel feature extraction for massive data sets. | Ivor W. Tsang, Andrs Kocsor, James T. Kwok |
| 2005 | AISTATS | Very Large SVM Training using Core Vector Machines. | Ivor W. Tsang, James Tin-Yau Kwok, Pak-Ming Cheung |
| 2005 | GLOBECOM | Position estimation for wireless sensor networks. | Kin Fung Simon Wong, Ivor W. Tsang, Victor Cheung, S.-H. Gary Chan, James T. Kwok |
| 2005 | ICML | Core Vector Regression for very large regression problems. | Ivor W. Tsang, James T. Kwok, Kimo T. Lai |
| 2004 | IJCNN | Scaling up support vector data description by using core-sets. | Calvin S. Chu, Ivor W. Tsang, James T. Kwok |
| 2003 | ICML | Learning with Idealized Kernels. | James T. Kwok, Ivor W. Tsang |
| 2003 | ICML | The Pre-Image Problem in Kernel Methods. | James T. Kwok, Ivor W. Tsang |