Learning with Idealized Kernels. - James T. Kwok; Ivor W. Tsang (ICML, 2003)

Linear dependency between ε and the input noise in ε-support vector regression. - James T. Kwok; Ivor W. Tsang (IEEE Trans. Neural Networks, 2003)

Scaling up support vector data description by using core-sets. - Calvin S. Chu; Ivor W. Tsang; James T. Kwok (IJCNN, 2004)

The pre-image problem in kernel methods. - James Tin-Yau Kwok; Ivor Wai-Hung Tsang (IEEE Trans. Neural Networks, 2004)

Fusing images with different focuses using support vector machines. - Shutao Li; James Tin-Yau Kwok; Ivor Wai-Hung Tsang; Yaonan Wang 001 (IEEE Trans. Neural Networks, 2004)

Very Large SVM Training using Core Vector Machines. - Ivor W. Tsang; James Tin-Yau Kwok; Pak-Ming Cheung (AISTATS, 2005)

Position estimation for wireless sensor networks. - Kin Fung Simon Wong; Ivor W. Tsang; Victor Cheung; S.-H. Gary Chan; James T. Kwok (GLOBECOM, 2005)

Core Vector Regression for very large regression problems. - Ivor W. Tsang; James T. Kwok; Kimo T. Lai (ICML, 2005)

Pattern de-noising based on support vector data description. - Jooyoung Park 001; Daesung Kang; Jongho Kim; James Tin-Yau Kwok; Ivor Wai-Hung Tsang (IJCNN, 2005)

Kernel relevant component analysis for distance metric learning. - Ivor Wai-Hung Tsang; Pak-Ming Cheung; James Tin-Yau Kwok (IJCNN, 2005)

Core Vector Machines: Fast SVM Training on Very Large Data Sets. - Ivor W. Tsang; James T. Kwok; Pak-Ming Cheung (J. Mach. Learn. Res., 2005)

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

Fast Speaker Adaption Via Maximum Penalized Likelihood Kernel Regression. - Ivor W. Tsang; James T. Kwok; Brian Mak; Kai Zhang 001; Jeffrey Junfeng Pan (ICASSP (1), 2006)

Learning the Kernel in Mahalanobis One-Class Support Vector Machines. - Ivor W. Tsang; James T. Kwok; Shutao Li (IJCNN, 2006)

Efficient kernel feature extraction for massive data sets. - Ivor W. Tsang; András Kocsor; James T. Kwok (KDD, 2006)

Large-Scale Sparsified Manifold Regularization. - Ivor W. Tsang; James T. Kwok (NIPS, 2006)

Efficient hyperkernel learning using second-order cone programming. - Ivor Wai-Hung Tsang; James Tin-Yau Kwok (IEEE Trans. Neural Networks, 2006)

Generalized Core Vector Machines. - Ivor Wai-Hung Tsang; James Tin-Yau Kwok; Jacek M. Zurada (IEEE Trans. Neural Networks, 2006)

Simpler core vector machines with enclosing balls. - Ivor W. Tsang; András Kocsor; James T. Kwok (ICML, 2007)

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

SVDD-Based Pattern Denoising. - Jooyoung Park 001; Daesung Kang; Jongho Kim; James T. Kwok; Ivor W. Tsang (Neural Comput., 2007)

A Class of Single-Class Minimax Probability Machines for Novelty Detection. - James T. Kwok; Ivor Wai-Hung Tsang; Jacek M. Zurada (IEEE Trans. Neural Networks, 2007)

Improved Nyström low-rank approximation and error analysis. - Kai Zhang 001; Ivor W. Tsang; James T. Kwok (ICML, 2008)

Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines. - Ivor Wai-Hung Tsang; András Kocsor; James Tin-Yau Kwok (IEEE Trans. Neural Networks, 2008)

Domain Transfer SVM for video concept detection. - Lixin Duan; Ivor Wai-Hung Tsang; Dong Xu 001; Stephen J. Maybank (CVPR, 2009)

Domain adaptation from multiple sources via auxiliary classifiers. - Lixin Duan; Ivor W. Tsang; Dong Xu 001; Tat-Seng Chua (ICML, 2009)

SimpleNPKL: simple non-parametric kernel learning. - Jinfeng Zhuang; Ivor W. Tsang; Steven C. H. Hoi (ICML, 2009)

Spectral Embedded Clustering. - Feiping Nie 001; Dong Xu 001; Ivor W. Tsang; Changshui Zhang (IJCAI, 2009)

Extracting discriminative concepts for domain adaptation in text mining. - Bo Chen; Wai Lam; Ivor W. Tsang; Tak-Lam Wong (KDD, 2009)

Using large-scale web data to facilitate textual query based retrieval of consumer photos. - Yiming Liu 001; Dong Xu 001; Ivor W. Tsang; Jiebo Luo 001 (ACM Multimedia, 2009)

T-IRS: textual query based image retrieval system for consumer photos. - Yiming Liu 001; Dong Xu 001; Ivor W. Tsang; Jiebo Luo 001 (ACM Multimedia, 2009)

A Convex Method for Locating Regions of Interest with Multi-instance Learning. - Yufeng Li 008; James T. Kwok; Ivor W. Tsang; Zhi-Hua Zhou (ECML/PKDD (2), 2009)

A Semi-Supervised Framework for Feature Mapping and Multiclass Classification. - Bo Chen; Wai Lam; Ivor W. Tsang; Tak-Lam Wong (SDM, 2009)

Tighter and Convex Maximum Margin Clustering. - Yufeng Li 008; Ivor W. Tsang; James Tin-Yau Kwok; Zhi-Hua Zhou (AISTATS, 2009)

Maximum Penalized Likelihood Kernel Regression for Fast Adaptation. - Brian Kan-Wing Mak; Tsz-Chung Lai; Ivor W. Tsang; James Tin-Yau Kwok (IEEE Trans. Speech Audio Process., 2009)

Maximum Margin Clustering Made Practical. - Kai Zhang 001; Ivor W. Tsang; James T. Kwok (IEEE Trans. Neural Networks, 2009)

Clustering-based methodology with minimal user supervision for displaying cell-phenotype signatures in image-based screening. - William-Chandra Tjhi; Gary Kee Khoon Lee; Terence Hung; Yew-Soon Ong; Ivor Wai-Hung Tsang; Victor Racine; Frédéric Bard (BIBM Workshops, 2010)

Tag-based web photo retrieval improved by batch mode re-tagging. - Lin Chen 021; Dong Xu 001; Ivor Wai-Hung Tsang; Jiebo Luo 001 (CVPR, 2010)

Local features are not lonely - Laplacian sparse coding for image classification. - Shenghua Gao; Ivor Wai-Hung Tsang; Liang-Tien Chia; Peilin Zhao (CVPR, 2010)

Kernel Sparse Representation for Image Classification and Face Recognition. - Shenghua Gao; Ivor Wai-Hung Tsang; Liang-Tien Chia (ECCV (4), 2010)

Location and Scatter Matching for Dataset Shift in Text Mining. - Bo Chen; Wai Lam; Ivor W. Tsang; Tak-Lam Wong (ICDM, 2010)

Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets. - Mingkui Tan; Li Wang 033; Ivor W. Tsang (ICML, 2010)

Automatic image tagging via category label and web data. - Shenghua Gao; Zhengxiang Wang; Liang-Tien Chia; Ivor Wai-Hung Tsang (ACM Multimedia, 2010)

Predictive Distribution Matching SVM for Multi-domain Learning. - Chun-Wei Seah; Ivor W. Tsang; Yew-Soon Ong; Gary Kee Khoon Lee (ECML/PKDD (1), 2010)

Parameter-Free Spectral Kernel Learning. - Qi Mao 001; Ivor W. Tsang (UAI, 2010)

Efficiently Learning Nonlinear Classifiers for Domain Specific Performance Measures - Nan Li 019; Ivor W. Tsang; Zhi-Hua Zhou (CoRR, 2010)

Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction. - Feiping Nie 001; Dong Xu 001; Ivor Wai-Hung Tsang; Changshui Zhang (IEEE Trans. Image Process., 2010)

Incorporating the loss function into discriminative clustering of structured outputs. - Wenliang Zhong; Weike Pan; James T. Kwok; Ivor W. Tsang (IEEE Trans. Neural Networks, 2010)

Multi-layer group sparse coding - For concurrent image classification and annotation. - Shenghua Gao; Liang-Tien Chia; Ivor Wai-Hung Tsang (CVPR, 2011)

Text-based image retrieval using progressive multi-instance learning. - Wen Li 001; Lixin Duan; Dong Xu 001; Ivor Wai-Hung Tsang (ICCV, 2011)

Optimizing Performance Measures for Feature Selection. - Qi Mao 001; Ivor Wai-Hung Tsang (ICDM, 2011)

Healing Sample Selection Bias by Source Classifier Selection. - Chun-Wei Seah; Ivor Wai-Hung Tsang; Yew-Soon Ong (ICDM, 2011)

Infinite Decision Agent Ensemble Learning System for Credit Risk Analysis. - Shukai Li; Ivor W. Tsang; Narendra S. Chaudhari (ICMLA (1), 2011)

Maximum Margin/Volume Outlier Detection. - Shukai Li; Ivor W. Tsang (ICTAI, 2011)

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

Multiple Template Learning for Structured Prediction - Qi Mao 001; Ivor W. Tsang (CoRR, 2011)

Exploratory analysis of cell-based screening data for phenotype identification in drug-siRNA study. - William-Chandra Tjhi; Gary Kee Khoon Lee; Terence Hung; Ivor Wai-Hung Tsang; Yew-Soon Ong; Frédéric Bard; Victor Racine (Int. J. Comput. Biol. Drug Des., 2011)

Learning to Locate Relative Outliers. - Shukai Li; Ivor W. Tsang (ACML, 2011)

A Family of Simple Non-Parametric Kernel Learning Algorithms. - Jinfeng Zhuang; Ivor W. Tsang; Steven C. H. Hoi (J. Mach. Learn. Res., 2011)

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

Textual Query of Personal Photos Facilitated by Large-Scale Web Data. - Yiming Liu 001; Dong Xu 001; Ivor W. Tsang; Jiebo Luo 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Improving Web Image Search by Bag-Based Reranking. - Lixin Duan; Wen Li 001; Ivor Wai-Hung Tsang; Dong Xu 001 (IEEE Trans. Image Process., 2011)

Spectral Embedded Clustering: A Framework for In-Sample and Out-of-Sample Spectral Clustering. - Feiping Nie 001; Zinan Zeng; Ivor W. Tsang; Dong Xu 001; Changshui Zhang (IEEE Trans. Neural Networks, 2011)

Domain Adaptation via Transfer Component Analysis. - Sinno Jialin Pan; Ivor W. Tsang; James T. Kwok; Qiang Yang 001 (IEEE Trans. Neural Networks, 2011)

A Hybrid PSO-BFGS Strategy for Global Optimization of Multimodal Functions. - Shutao Li; Mingkui Tan; Ivor W. Tsang; James Tin-Yau Kwok (IEEE Trans. Syst. Man Cybern. Part B, 2011)

Convex Matching Pursuit for Large-Scale Sparse Coding and Subset Selection. - Mingkui Tan; Ivor W. Tsang; Li Wang 033; Xinming Zhang (AAAI, 2012)

Efficient Discriminative Learning of Class Hierarchy for Many Class Prediction. - Lin Chen 021; Lixin Duan; Ivor W. Tsang; Dong Xu 001 (ACCV (1), 2012)

An evolutionary search paradigm that learns with past experiences. - Liang Feng 001; Yew-Soon Ong; Ivor Wai-Hung Tsang; Ah-Hwee Tan (IEEE Congress on Evolutionary Computation, 2012)

Pareto Rank Learning in Multi-objective Evolutionary Algorithms. - Chun-Wei Seah; Yew-Soon Ong; Ivor W. Tsang; Siwei Jiang (IEEE Congress on Evolutionary Computation, 2012)

Batch mode Adaptive Multiple Instance Learning for computer vision tasks. - Wen Li 001; Lixin Duan; Ivor Wai-Hung Tsang; Dong Xu 001 (CVPR, 2012)

Domain Adaptation for Coreference Resolution: An Adaptive Ensemble Approach. - Jian-Bo Yang; Qi Mao 001; Qiaoliang Xiang; Ivor Wai-Hung Tsang; Kian Ming Adam Chai; Hai Leong Chieu (EMNLP-CoNLL, 2012)

Co-labeling: A New Multi-view Learning Approach for Ambiguous Problems. - Wen Li 001; Lixin Duan; Ivor Wai-Hung Tsang; Dong Xu 001 (ICDM, 2012)

Learning Target Predictive Function without Target Labels. - Chun-Wei Seah; Ivor Wai-Hung Tsang; Yew-Soon Ong; Qi Mao 001 (ICDM, 2012)

Handling Ambiguity via Input-Output Kernel Learning. - Xinxing Xu; Ivor W. Tsang; Dong Xu 001 (ICDM, 2012)

Learning with Augmented Features for Heterogeneous Domain Adaptation. - Lixin Duan; Dong Xu 001; Ivor W. Tsang (ICML, 2012)

A Split-Merge Framework for Comparing Clusterings. - Qiaoliang Xiang; Qi Mao 001; Kian Ming Adam Chai; Hai Leong Chieu; Ivor W. Tsang; Zhendong Zhao (ICML, 2012)

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

Meme as Building Block for Evolutionary Optimization of Problem Instances - Liang Feng 001; Yew-Soon Ong; Ah-Hwee Tan; Ivor Wai-Hung Tsang (CoRR, 2012)

Towards Large-scale and Ultrahigh Dimensional Feature Selection via Feature Generation - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (CoRR, 2012)

Relevance vector machine based infinite decision agent ensemble learning for credit risk analysis. - Shukai Li; Ivor W. Tsang; Narendra S. Chaudhari (Expert Syst. Appl., 2012)

Multi-view Positive and Unlabeled Learning. - Joey Tianyi Zhou; Sinno Jialin Pan; Qi Mao 001; Ivor W. Tsang (ACML, 2012)

Domain Transfer Multiple Kernel Learning. - Lixin Duan; Ivor W. Tsang; Dong Xu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Visual Event Recognition in Videos by Learning from Web Data. - Lixin Duan; Dong Xu 001; Ivor Wai-Hung Tsang; Jiebo Luo 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Tag-Based Image Retrieval Improved by Augmented Features and Group-Based Refinement. - Lin Chen 021; Dong Xu 001; Ivor W. Tsang; Jiebo Luo 001 (IEEE Trans. Multim., 2012)

Laplacian Embedded Regression for Scalable Manifold Regularization. - Lin Chen 021; Ivor W. Tsang; Dong Xu 001 (IEEE Trans. Neural Networks Learn. Syst., 2012)

Domain Adaptation From Multiple Sources: A Domain-Dependent Regularization Approach. - Lixin Duan; Dong Xu 001; Ivor Wai-Hung Tsang (IEEE Trans. Neural Networks Learn. Syst., 2012)

Transductive Ordinal Regression. - Chun-Wei Seah; Ivor W. Tsang; Yew-Soon Ong (IEEE Trans. Neural Networks Learn. Syst., 2012)

Feature Weighting via Optimal Thresholding for Video Analysis. - Zhongwen Xu; Yi Yang 001; Ivor W. Tsang; Nicu Sebe; Alexander G. Hauptmann (ICCV, 2013)

Is Matching Pursuit Solving Convex Problems? - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (CoRR, 2013)

Convex and scalable weakly labeled SVMs. - Yufeng Li 008; Ivor W. Tsang; James T. Kwok; Zhi-Hua Zhou (J. Mach. Learn. Res., 2013)

Discovering Low-Rank Shared Concept Space for Adapting Text Mining Models. - Bo Chen; Wai Lam; Ivor W. Tsang; Tak-Lam Wong (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Laplacian Sparse Coding, Hypergraph Laplacian Sparse Coding, and Applications. - Shenghua Gao; Ivor Wai-Hung Tsang; Liang-Tien Chia (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Efficient Optimization of Performance Measures by Classifier Adaptation. - Nan Li 019; Ivor W. Tsang; Zhi-Hua Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

A Feature Selection Method for Multivariate Performance Measures. - Qi Mao 001; Ivor Wai-Hung Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Combating Negative Transfer From Predictive Distribution Differences. - Chun-Wei Seah; Yew-Soon Ong; Ivor W. Tsang (IEEE Trans. Cybern., 2013)

Sparse Representation With Kernels. - Shenghua Gao; Ivor Wai-Hung Tsang; Liang-Tien Chia (IEEE Trans. Image Process., 2013)

Objective-Guided Image Annotation. - Qi Mao 001; Ivor Wai-Hung Tsang; Shenghua Gao (IEEE Trans. Image Process., 2013)

Efficient Multitemplate Learning for Structured Prediction. - Qi Mao 001; Ivor Wai-Hung Tsang (IEEE Trans. Neural Networks Learn. Syst., 2013)

Transfer Ordinal Label Learning. - Chun-Wei Seah; Ivor W. Tsang; Yew-Soon Ong (IEEE Trans. Neural Networks Learn. Syst., 2013)

Minimax Sparse Logistic Regression for Very High-Dimensional Feature Selection. - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (IEEE Trans. Neural Networks Learn. Syst., 2013)

Soft Margin Multiple Kernel Learning. - Xinxing Xu; Ivor W. Tsang; Dong Xu 001 (IEEE Trans. Neural Networks Learn. Syst., 2013)

Hybrid Heterogeneous Transfer Learning through Deep Learning. - Joey Tianyi Zhou; Sinno Jialin Pan; Ivor W. Tsang; Yan Yan 006 (AAAI, 2014)

Deep Representations to Model User 'Likes'. - Sharath Chandra Guntuku; Joey Tianyi Zhou; Sujoy Roy; Weisi Lin; Ivor W. Tsang (ACCV (1), 2014)

Robust Domain Adaptation for Relation Extraction via Clustering Consistency. - Minh Luan Nguyen; Ivor W. Tsang; Kian Ming Adam Chai; Hai Leong Chieu (ACL (1), 2014)

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

Event Detection Using Multi-level Relevance Labels and Multiple Features. - Zhongwen Xu; Ivor W. Tsang; Yi Yang 001; Zhigang Ma; Alexander G. Hauptmann (CVPR, 2014)

Feature Disentangling Machine - A Novel Approach of Feature Selection and Disentangling in Facial Expression Analysis. - Ping Liu 004; Joey Tianyi Zhou; Ivor Wai-Hung Tsang; Zibo Meng; Shizhong Han; Yan Tong (ECCV (4), 2014)

Riemannian Pursuit for Big Matrix Recovery. - Mingkui Tan; Ivor W. Tsang; Li Wang 033; Bart Vandereycken; Sinno Jialin Pan (ICML, 2014)

The Emerging ?Big Dimensionality? - Yiteng Zhai; Yew-Soon Ong; Ivor W. Tsang (IEEE Comput. Intell. Mag., 2014)

Towards ultrahigh dimensional feature selection for big data. - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (J. Mach. Learn. Res., 2014)

Learning With Augmented Features for Supervised and Semi-Supervised Heterogeneous Domain Adaptation. - Wen Li 001; Lixin Duan; Dong Xu 001; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Region-Based Saliency Detection and Its Application in Object Recognition. - Zhixiang Ren; Shenghua Gao; Liang-Tien Chia; Ivor Wai-Hung Tsang (IEEE Trans. Circuits Syst. Video Technol., 2014)

Spectral Embedded Hashing for Scalable Image Retrieval. - Lin Chen 021; Dong Xu 001; Ivor Wai-Hung Tsang; Xuelong Li 001 (IEEE Trans. Cybern., 2014)

Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization. - Shenghua Gao; Ivor Wai-Hung Tsang; Yi Ma 001 (IEEE Trans. Image Process., 2014)

Concurrent Single-Label Image Classification and Annotation via Efficient Multi-Layer Group Sparse Coding. - Shenghua Gao; Liang-Tien Chia; Ivor Wai-Hung Tsang; Zhixiang Ren (IEEE Trans. Multim., 2014)

Effectively Predicting Whether and When a Topic Will Become Prevalent in a Social Network. - Weiwei Liu 003; Zhi-Hong Deng 001; Xiuwen Gong; Frank Jiang 001; Ivor W. Tsang (AAAI, 2015)

Large Margin Metric Learning for Multi-Label Prediction. - Weiwei Liu 003; Ivor W. Tsang (AAAI, 2015)

Defragging Subgraph Features for Graph Classification. - Haishuai Wang; Peng Zhang 001; Ivor W. Tsang; Ling Chen 006; Chengqi Zhang (CIKM, 2015)

Objects co-segmentation: Propagated from simpler images. - Marcus Chen; Santiago Velasco-Forero; Ivor W. Tsang; Tat-Jen Cham (ICASSP, 2015)

Scalable Maximum Margin Matrix Factorization by Active Riemannian Subspace Search. - Yan Yan 006; Mingkui Tan; Ivor W. Tsang; Yi Yang 001; Chengqi Zhang; Qinfeng Shi (IJCAI, 2015)

On the Optimality of Classifier Chain for Multi-label Classification. - Weiwei Liu 003; Ivor W. Tsang (NIPS, 2015)

A Novel Regularized Principal Graph Learning Framework on Explicit Graph Representation. - Qi Mao 001; Li Wang 033; Ivor W. Tsang; Yijun Sun (CoRR, 2015)

Memes as building blocks: a case study on evolutionary optimization + transfer learning for routing problems. - Liang Feng 001; Yew-Soon Ong; Ah-Hwee Tan; Ivor W. Tsang (Memetic Comput., 2015)

Memetic Search With Interdomain Learning: A Realization Between CVRP and CARP. - Liang Feng 001; Yew-Soon Ong; Meng-Hiot Lim; Ivor W. Tsang (IEEE Trans. Evol. Comput., 2015)

A Unified Feature Selection Framework for Graph Embedding on High Dimensional Data. - Marcus Chen; Ivor W. Tsang; Mingkui Tan; Cham Tat Jen (IEEE Trans. Knowl. Data Eng., 2015)

Generalized Multiple Kernel Learning With Data-Dependent Priors. - Qi Mao 001; Ivor W. Tsang; Shenghua Gao; Li Wang 033 (IEEE Trans. Neural Networks Learn. Syst., 2015)

Matching Pursuit LASSO Part I: Sparse Recovery Over Big Dictionary. - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (IEEE Trans. Signal Process., 2015)

Matching Pursuit LASSO Part II: Applications and Sparse Recovery Over Batch Signals. - Mingkui Tan; Ivor W. Tsang; Li Wang 033 (IEEE Trans. Signal Process., 2015)

Sparse Perceptron Decision Tree for Millions of Dimensions. - Weiwei Liu 003; Ivor W. Tsang (AAAI, 2016)

Learning Sparse Confidence-Weighted Classifier on Very High Dimensional Data. - Mingkui Tan; Yan Yan 006; Li Wang 033; Anton van den Hengel; Ivor W. Tsang; Qinfeng (Javen) Shi (AAAI, 2016)

Optimizing Multivariate Performance Measures from Multi-View Data. - Jim Jing-Yan Wang; Ivor Wai-Hung Tsang; Xin Gao 001 (AAAI, 2016)

Robust Semi-Supervised Learning through Label Aggregation. - Yan Yan 006; Zhongwen Xu; Ivor W. Tsang; Guodong Long; Yi Yang 001 (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, 2016)

Inferring Latent Network from Cascade Data for Dynamic Social Recommendation. - Qin Zhang 011; Jia Wu 001; Peng Zhang 001; Guodong Long; Ivor W. Tsang; Chengqi Zhang (ICDM, 2016)

Transfer Hashing with Privileged Information. - Joey Tianyi Zhou; Xinxing Xu; Sinno Jialin Pan; Ivor W. Tsang; Zheng Qin 004; Rick Siow Mong Goh (IJCAI, 2016)

On the Convergence of a Family of Robust Losses for Stochastic Gradient Descent. - Bo Han 003; Ivor W. Tsang; Ling Chen 006 (ECML/PKDD (1), 2016)

Simple and Efficient Learning using Privileged Information. - Xinxing Xu; Joey Tianyi Zhou; Ivor W. Tsang; Zheng Qin 004; Rick Siow Mong Goh; Yong Liu 026 (CoRR, 2016)

N-ary Error Correcting Coding Scheme. - Joey Tianyi Zhou; Ivor W. Tsang; Shen-Shyang Ho; Klaus-Robert Müller (CoRR, 2016)

Learning word dependencies in text by means of a deep recurrent belief network. - Iti Chaturvedi; Yew-Soon Ong; Ivor W. Tsang; Roy E. Welsch; Erik Cambria (Knowl. Based Syst., 2016)

Co-Labeling for Multi-View Weakly Labeled Learning. - Xinxing Xu; Wen Li 001; Dong Xu 001; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Making Trillion Correlations Feasible in Feature Grouping and Selection. - Yiteng Zhai; Yew-Soon Ong; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

DEFEATnet - A Deep Conventional Image Representation for Image Classification. - Shenghua Gao; Lixin Duan; Ivor W. Tsang (IEEE Trans. Circuits Syst. Video Technol., 2016)

Understanding Deep Representations Learned in Modeling Users Likes. - Sharath Chandra Guntuku; Joey Tianyi Zhou; Sujoy Roy; Weisi Lin; Ivor W. Tsang (IEEE Trans. Image Process., 2016)

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 003; Ivor W. Tsang; Fumin Shen; Quan-Sen Sun (AAAI, 2017)

Latent Smooth Skeleton Embedding. - Li Wang 033; Qi Mao 001; Ivor W. Tsang (AAAI, 2017)

Compact Multiple-Instance Learning. - Jing Chai; Weiwei Liu 003; Ivor W. Tsang; Xiao-Bo Shen (CIKM, 2017)

Discovering User Interests from Social Images. - Jiangchao Yao; Ya Zhang 002; Ivor W. Tsang; Jun Sun 005 (MMM (2), 2017)

Sparse Embedded k-Means Clustering. - Weiwei Liu 003; Xiao-Bo Shen; Ivor W. Tsang (NIPS, 2017)

Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions. - Weiwei Liu 003; Ivor W. Tsang (J. Mach. Learn. Res., 2017)

An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels. - Weiwei Liu 003; Ivor W. Tsang; Klaus-Robert Müller (J. Mach. Learn. Res., 2017)

A unified probabilistic framework for robust manifold learning and embedding. - Qi Mao 001; Li Wang 033; Ivor W. Tsang (Mach. Learn., 2017)

Principal Graph and Structure Learning Based on Reversed Graph Embedding. - Qi Mao 001; Li Wang 033; Ivor W. Tsang; Yijun Sun (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Multi-instance dictionary learning via multivariate performance measure optimization. - Jim Jing-Yan Wang; Ivor Wai-Hung Tsang; Xuefeng Cui; Zhiwu Lu 001; Xin Gao 001 (Pattern Recognit., 2017)

Partial Hash Update via Hamming Subspace Learning. - Chao Ma 002; Ivor W. Tsang; Furong Peng; Chuancai Liu (IEEE Trans. Image Process., 2017)

Incremental Subgraph Feature Selection for Graph Classification. - Haishuai Wang; Peng Zhang 001; Xingquan Zhu 001; Ivor Wai-Hung Tsang; Ling Chen 006; Chengqi Zhang; Xindong Wu 001 (IEEE Trans. Knowl. Data Eng., 2017)

Compact Multi-Label Learning. - Xiaobo Shen 001; Weiwei Liu 003; Ivor W. Tsang; Quan-Sen Sun; Yew-Soon Ong (AAAI, 2018)

Doubly Approximate Nearest Neighbor Classification. - Weiwei Liu 003; Zhuanghua Liu; Ivor W. Tsang; Wenjie Zhang 001; Xuemin Lin 001 (AAAI, 2018)

SC2Net: Sparse LSTMs for Sparse Coding. - Joey Tianyi Zhou; Kai Di; Jiawei Du; Xi Peng 001; Hao Yang 033; Sinno Jialin Pan; Ivor W. Tsang; Yong Liu 026; Zheng Qin 004; Rick Siow Mong Goh (AAAI, 2018)

An Efficient Exact Nearest Neighbor Search by Compounded Embedding. - Mingjie Li 004; Ying Zhang 001; Yifang Sun; Wei Wang 011; Ivor W. Tsang; Xuemin Lin 001 (DASFAA (1), 2018)

Deep Discrete Prototype Multilabel Learning. - Xiaobo Shen 001; Weiwei Liu 003; Yong Luo 002; Yew-Soon Ong; Ivor W. Tsang (IJCAI, 2018)

Towards the Learning of Weighted Multi-label Associative Classifiers. - Chunyang Liu; Ling Chen 006; Ivor W. Tsang; Hongzhi Yin (IJCNN, 2018)

High-order Proximity Preserving Information Network Hashing. - Defu Lian; Kai Zheng 001; Vincent W. Zheng; Yong Ge; Longbing Cao; Ivor W. Tsang; Xing Xie 001 (KDD, 2018)

Discrete Ranking-based Matrix Factorization with Self-Paced Learning. - Yan Zhang 036; Haoyu Wang 004; Defu Lian; Ivor W. Tsang; Hongzhi Yin; Guowu Yang (KDD, 2018)

Masking: A New Perspective of Noisy Supervision. - Bo Han 003; Jiangchao Yao; Gang Niu 001; Mingyuan Zhou; Ivor W. Tsang; Ya Zhang 002; Masashi Sugiyama (NeurIPS, 2018)

Co-teaching: Robust training of deep neural networks with extremely noisy labels. - Bo Han 003; Quanming Yao; Xingrui Yu; Gang Niu 001; Miao Xu 001; Weihua Hu; Ivor W. Tsang; Masashi Sugiyama (NeurIPS, 2018)

Degeneration in VAE: in the Light of Fisher Information Loss. - Huangjie Zheng; Jiangchao Yao; Ya Zhang 002; Ivor W. Tsang (CoRR, 2018)

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. - Fanhua Shang; Kaiwen Zhou; James Cheng; Ivor W. Tsang; Lijun Zhang 005; Dacheng Tao (CoRR, 2018)

Variational Composite Autoencoders. - Jiangchao Yao; Ivor W. Tsang; Ya Zhang 002 (CoRR, 2018)

Zero-shot Learning with Complementary Attributes. - Xiaofeng Xu; Ivor W. Tsang; Chuancai Liu (CoRR, 2018)

Co-sampling: Training Robust Networks for Extremely Noisy Supervision. - Bo Han 003; Quanming Yao; Xingrui Yu; Gang Niu 001; Miao Xu 001; Weihua Hu; Ivor W. Tsang; Masashi Sugiyama (CoRR, 2018)

Multi-Context Label Embedding. - Yaxin Shi; Donna Xu; Yuangang Pan; Ivor W. Tsang (CoRR, 2018)

Matrix Co-completion for Multi-label Classification with Missing Features and Labels. - Miao Xu 001; Gang Niu 001; Bo Han 003; Ivor W. Tsang; Zhi-Hua Zhou; Masashi Sugiyama (CoRR, 2018)

Understanding VAEs in Fisher-Shannon Plane. - Huangjie Zheng; Jiangchao Yao; Ya Zhang 002; Ivor W. Tsang (CoRR, 2018)

Pumpout: A Meta Approach for Robustly Training Deep Neural Networks with Noisy Labels. - Bo Han 003; Gang Niu 001; Jiangchao Yao; Xingrui Yu; Miao Xu 001; Ivor W. Tsang; Masashi Sugiyama (CoRR, 2018)

Robust Plackett-Luce model for k-ary crowdsourced preferences. - Bo Han 003; Yuangang Pan; Ivor W. Tsang (Mach. Learn., 2018)

Stagewise learning for noisy k-ary preferences. - Yuangang Pan; Bo Han 003; Ivor W. Tsang (Mach. Learn., 2018)

'Who Likes What and, Why?' Insights into Modeling Users' Personality Based on Image 'Likes'. - Sharath Chandra Guntuku; Joey Tianyi Zhou; Sujoy Roy; Weisi Lin; Ivor W. Tsang (IEEE Trans. Affect. Comput., 2018)

Online Product Quantization. - Donna Xu; Ivor W. Tsang; Ying Zhang 001 (IEEE Trans. Knowl. Data Eng., 2018)

Progressive Stochastic Learning for Noisy Labels. - Bo Han 003; Ivor W. Tsang; Ling Chen 006; Celina Ping Yu; Sai-Fu Fung (IEEE Trans. Neural Networks Learn. Syst., 2018)

Multilabel Prediction via Cross-View Search. - Xiaobo Shen 001; Weiwei Liu 003; Ivor W. Tsang; Quan-Sen Sun; Yew-Soon Ong (IEEE Trans. Neural Networks Learn. Syst., 2018)

Online Heterogeneous Transfer by Hedge Ensemble of Offline and Online Decisions. - Yuguang Yan; Qingyao Wu; Mingkui Tan; Michael K. Ng 001; Huaqing Min; Ivor W. Tsang (IEEE Trans. Neural Networks Learn. Syst., 2018)

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

Safeguarded Dynamic Label Regression for Noisy Supervision. - Jiangchao Yao; Hao Wu 075; Ya Zhang 002; Ivor W. Tsang; Jun Sun 005 (AAAI, 2019)

Understanding VAEs in Fisher-Shannon Plane. - Huangjie Zheng; Jiangchao Yao; Ya Zhang 002; Ivor W. Tsang; Jia Wang (AAAI, 2019)

Long-short Distance Aggregation Networks for Positive Unlabeled Graph Learning. - Man Wu; Shirui Pan; Lan Du 002; Ivor W. Tsang; Xingquan Zhu 001; Bo Du 001 (CIKM, 2019)

Marginalized Average Attentional Network for Weakly-Supervised Learning. - Yuan Yuan 002; Yueming Lyu; Xi Shen 001; Ivor W. Tsang; Dit-Yan Yeung (ICLR (Poster), 2019)

How does Disagreement Help Generalization against Label Corruption? - Xingrui Yu; Bo Han 003; Jiangchao Yao; Gang Niu 001; Ivor W. Tsang; Masashi Sugiyama (ICML, 2019)

Support Matching: A Novel Regularization to Escape from Mode Collapse in GANs. - Yinghua Yao; Yuangang Pan; Ivor W. Tsang; Xin Yao 001 (ICONIP (4), 2019)

Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation. - Xiaofeng Xu; Ivor W. Tsang; Xiaofeng Cao 002; Ruiheng Zhang 001; Chuancai Liu (IJCAI, 2019)

Rectified Encoder Network for High-Dimensional Imbalanced Learning. - Tao Zheng; Wei-Jie Chen 001; Ivor W. Tsang; Xin Yao 001 (PRICAI (2), 2019)

A deep learning framework for Hybrid Heterogeneous Transfer Learning. - Joey Tianyi Zhou; Sinno Jialin Pan; Ivor W. Tsang (Artif. Intell., 2019)

Efficient Batch Black-box Optimization with Deterministic Regret Bounds. - Yueming Lyu; Yuan Yuan 002; Ivor W. Tsang (CoRR, 2019)

Probabilistic CCA with Implicit Distributions. - Yaxin Shi; Yuangang Pan; Donna Xu; Ivor W. Tsang (CoRR, 2019)

Latent Adversarial Defence with Boundary-guided Generation. - Xiaowei Zhou 003; Ivor W. Tsang; Jie Yin 001 (CoRR, 2019)

Node Attribute Generation on Graphs. - Xu Chen 026; Siheng Chen; Huangjie Zheng; Jiangchao Yao; Kenan Cui; Ya Zhang 002; Ivor W. Tsang (CoRR, 2019)

Stochastic Implicit Natural Gradient for Black-box Optimization. - Yueming Lyu; Ivor W. Tsang (CoRR, 2019)

A Data-Analytics Approach for Enterprise Resilience. - Donna Xu; Ivor W. Tsang; Eng K. Chew; Cosimo Siclari; Varun Kaul (IEEE Intell. Syst., 2019)

Multi-class Heterogeneous Domain Adaptation. - Joey Tianyi Zhou; Ivor W. Tsang; Sinno Jialin Pan; Mingkui Tan (J. Mach. Learn. Res., 2019)

Millionaire: a hint-guided approach for crowdsourcing. - Bo Han 003; Quanming Yao; Yuangang Pan; Ivor W. Tsang; Xiaokui Xiao; Qiang Yang 001; Masashi Sugiyama (Mach. Learn., 2019)

N-ary decomposition for multi-class classification. - Joey Tianyi Zhou; Ivor W. Tsang; Shen-Shyang Ho; Klaus-Robert Müller (Mach. Learn., 2019)

Metric Learning for Multi-Output Tasks. - Weiwei Liu 003; Donna Xu; Ivor W. Tsang; Wenjie Zhang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Auto-weighted multi-view clustering via kernelized graph learning. - Shudong Huang; Zhao Kang 001; Ivor W. Tsang; Zenglin Xu (Pattern Recognit., 2019)

Error Correcting Input and Output Hashing. - Chao Ma 002; Ivor W. Tsang; Fumin Shen; Chuancai Liu (IEEE Trans. Cybern., 2019)

Well-M3N: A Maximum-Margin Approach to Unsupervised Structured Prediction. - Shaukat R. Abidi; Massimo Piccardi; Ivor W. Tsang; Mary-Anne Williams (IEEE Trans. Emerg. Top. Comput. Intell., 2019)

Late Fusion via Subspace Search With Consistency Preservation. - Xuanyi Dong; Yan Yan 006; Mingkui Tan; Yi Yang 001; Ivor W. Tsang (IEEE Trans. Image Process., 2019)

Hyperspectral Imagery Classification via Stochastic HHSVMs. - Weiwei Liu 003; Xiaobo Shen 001; Bo Du 001; Ivor W. Tsang; Wenjie Zhang 001; Xuemin Lin 001 (IEEE Trans. Image Process., 2019)

Deep Learning From Noisy Image Labels With Quality Embedding. - Jiangchao Yao; Jiajie Wang; Ivor W. Tsang; Ya Zhang 002; Jun Sun 005; Chengqi Zhang; Rui Zhang (IEEE Trans. Image Process., 2019)

Domain Adaption via Feature Selection on Explicit Feature Map. - Wan-Yu Deng; Amaury Lendasse; Yew-Soon Ong; Ivor Wai-Hung Tsang; Lin Chen 005; Qing-Hua Zheng (IEEE Trans. Neural Networks Learn. Syst., 2019)

Beyond Majority Voting: A Coarse-to-Fine Label Filtration for Heavily Noisy Labels. - Bo Han 003; Ivor W. Tsang; Ling Chen 006; Joey Tianyi Zhou; Celina Ping Yu (IEEE Trans. Neural Networks Learn. Syst., 2019)

An Empirical Study of Code Deobfuscations on Detecting Obfuscated Android Piggybacked Apps. - Yanxin Zhang; Guanping Xiao; Zheng Zheng 001; Tianqing Zhu; Ivor W. Tsang; Yulei Sui (APSEC, 2020)

Copy and Paste GAN: Face Hallucination From Shaded Thumbnails. - Yang Zhang 067; Ivor W. Tsang; Yawei Luo; Chang-Hui Hu 001; Xiaobo Lu; Xin Yu 002 (CVPR, 2020)

I/O Efficient Approximate Nearest Neighbour Search based on Learned Functions. - Mingjie Li 004; Ying Zhang 001; Yifang Sun; Wei Wang 011; Ivor W. Tsang; Xuemin Lin 001 (ICDE, 2020)

Curriculum Loss: Robust Learning and Generalization against Label Corruption. - Yueming Lyu; Ivor W. Tsang (ICLR, 2020)

SIGUA: Forgetting May Make Learning with Noisy Labels More Robust. - Bo Han 003; Gang Niu 001; Xingrui Yu; Quanming Yao; Miao Xu 001; Ivor W. Tsang; Masashi Sugiyama (ICML, 2020)

Intrinsic Reward Driven Imitation Learning via Generative Model. - Xingrui Yu; Yueming Lyu; Ivor W. Tsang (ICML, 2020)

Graph Cross Networks with Vertex Infomax Pooling. - Maosen Li; Siheng Chen; Ya Zhang 002; Ivor W. Tsang (NeurIPS, 2020)

Subgroup-based Rank-1 Lattice Quasi-Monte Carlo. - Yueming Lyu; Yuan Yuan 002; Ivor W. Tsang (NeurIPS, 2020)

Towards Sharper First-Order Adversary with Quantized Gradients. - Zhuanghua Liu; Ivor W. Tsang (CoRR, 2020)

Multi-view Alignment and Generation in CCA via Consistent Latent Encoding. - Yaxin Shi; Yuangang Pan; Donna Xu; Ivor W. Tsang (CoRR, 2020)

Learning Robust Node Representations on Graphs. - Xu Chen 026; Ya Zhang 002; Ivor W. Tsang; Yuangang Pan (CoRR, 2020)

Towards Equivalent Transformation of User Preferences in Cross Domain Recommendation. - Xu Chen 026; Ya Zhang 002; Ivor W. Tsang; Yuangang Pan; Jingchao Su (CoRR, 2020)

Deep N-ary Error Correcting Output Codes. - Hao Zhang 048; Joey Tianyi Zhou; Tianying Wang; Ivor W. Tsang; Rick Siow Mong Goh (CoRR, 2020)

A Survey of Label-noise Representation Learning: Past, Present and Future. - Bo Han 003; Quanming Yao; Tongliang Liu; Gang Niu 001; Ivor W. Tsang; James T. Kwok; Masashi Sugiyama (CoRR, 2020)

Collaborative Generative Hashing for Marketing and Fast Cold-Start Recommendation. - Yan Zhang 036; Ivor W. Tsang; Lixin Duan (IEEE Intell. Syst., 2020)

Auto-weighted multi-view co-clustering with bipartite graphs. - Shudong Huang; Zenglin Xu; Ivor W. Tsang; Zhao Kang 001 (Inf. Sci., 2020)

Stochastic Multichannel Ranking with Brain Dynamics Preferences. - Yuangang Pan; Ivor W. Tsang; Avinash Kumar Singh; Chin-Teng Lin; Masashi Sugiyama (Neural Comput., 2020)

Multiview Alignment and Generation in CCA via Consistent Latent Encoding. - Yaxin Shi; Yuangang Pan; Donna Xu; Ivor W. Tsang (Neural Comput., 2020)

Improving Generalization via Attribute Selection on Out-of-the-Box Data. - Xiaofeng Xu; Ivor W. Tsang; Chuancai Liu (Neural Comput., 2020)

Unseen Land Cover Classification from High-Resolution Orthophotos Using Integration of Zero-Shot Learning and Convolutional Neural Networks. - Biswajeet Pradhan; Husam Abdulrasool H. Al-Najjar; Maher Ibrahim Sameen; Ivor W. Tsang; Abdullah M. Alamri (Remote. Sens., 2020)

Secure Metric Learning via Differential Pairwise Privacy. - Jing Li 009; Yuangang Pan; Yulei Sui; Ivor W. Tsang (IEEE Trans. Inf. Forensics Secur., 2020)

Familial Clustering for Weakly-Labeled Android Malware Using Hybrid Representation Learning. - Yanxin Zhang; Yulei Sui; Shirui Pan; Zheng Zheng 001; Baodi Ning; Ivor W. Tsang; Wanlei Zhou 001 (IEEE Trans. Inf. Forensics Secur., 2020)

VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning. - Fanhua Shang; Kaiwen Zhou; Hongying Liu 001; James Cheng; Ivor W. Tsang; Lijun Zhang 005; Dacheng Tao; Licheng Jiao (IEEE Trans. Knowl. Data Eng., 2020)

Fast and Low Memory Cost Matrix Factorization: Algorithm, Analysis, and Case Study. - Yan Yan 006; Mingkui Tan; Ivor W. Tsang; Yi Yang 001; Qinfeng Shi; Chengqi Zhang (IEEE Trans. Knowl. Data Eng., 2020)

Guest Editorial Special Issue on Structured Multi-Output Learning: Modeling, Algorithm, Theory, and Applications. - Weiwei Liu 003; Xiaobo Shen 001; Yew-Soon Ong; Ivor W. Tsang; Chen Gong 002; Vladimir Pavlovic 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

Large Margin Partial Label Machine. - Jing Chai; Ivor W. Tsang; Weijie Chen 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

Survey on Multi-Output Learning. - Donna Xu; Yaxin Shi; Ivor W. Tsang; Yew-Soon Ong; Chen Gong 002; Xiaobo Shen 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting. - Jinliang Deng; Xiusi Chen; Renhe Jiang; Xuan Song 001; Ivor W. Tsang (KDD, 2021)

CDD: Multi-view Subspace Clustering via Cross-view Diversity Detection. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001; Quanhui Liu (ACM Multimedia, 2021)

Human-Understandable Decision Making for Visual Recognition. - Xiaowei Zhou 003; Jie Yin 001; Ivor W. Tsang; Chen Wang 008 (PAKDD (3), 2021)

Black-Box Optimizer with Stochastic Implicit Natural Gradient. - Yueming Lyu; Ivor W. Tsang (ECML/PKDD (3), 2021)

Generative Transition Mechanism to Image-to-Image Translation via Encoded Transformation. - Yaxin Shi; Xiaowei Zhou 003; Ping Liu 004; Ivor W. Tsang (CoRR, 2021)

Bayesian Active Learning by Disagreements: A Geometric Perspective. - Xiaofeng Cao 002; Ivor W. Tsang (CoRR, 2021)

Contrastive Conditional Transport for Representation Learning. - Huangjie Zheng; Xu Chen 026; Jiangchao Yao; Hongxia Yang; Chunyuan Li; Ya Zhang 002; Hao Zhang 050; Ivor W. Tsang; Jingren Zhou 001; Mingyuan Zhou (CoRR, 2021)

Neural Optimization Kernel: Towards Robust Deep Learning. - Yueming Lyu; Ivor W. Tsang (CoRR, 2021)

Imitation Learning: Progress, Taxonomies and Opportunities. - Boyuan Zheng; Sunny Verma; Jianlong Zhou; Ivor W. Tsang; Fang Chen 001 (CoRR, 2021)

Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network. - Maosen Li; Siheng Chen; Yanning Shen; Genjia Liu; Ivor W. Tsang; Ya Zhang 002 (CoRR, 2021)

TRIP: Refining Image-to-Image Translation via Rival Preferences. - Yinghua Yao; Yuangang Pan; Ivor W. Tsang; Xin Yao 001 (CoRR, 2021)

Online Mental Fatigue Monitoring via Indirect Brain Dynamics Evaluation. - Yuangang Pan; Ivor W. Tsang; Yueming Lyu; Avinash Kumar Singh; Chin-Teng Lin (Neural Comput., 2021)

Complementary Attributes: A New Clue to Zero-Shot Learning. - Xiaofeng Xu; Ivor W. Tsang; Chuancai Liu (IEEE Trans. Cybern., 2021)

Face Hallucination With Finishing Touches. - Yang Zhang 067; Ivor W. Tsang; Jun Li 010; Ping Liu 004; Xiaobo Lu; Xin Yu 002 (IEEE Trans. Image Process., 2021)

The Pulse of Urban Transport: Exploring the Co-evolving Pattern for Spatio-temporal Forecasting. - Jinliang Deng; Xiusi Chen; Zipei Fan; Renhe Jiang; Xuan Song 001; Ivor W. Tsang (ACM Trans. Knowl. Discov. Data, 2021)

Privacy-Preserving Stochastic Gradual Learning. - Bo Han 003; Ivor W. Tsang; Xiaokui Xiao; Ling Chen 006; Sai-Fu Fung; Celina Ping Yu (IEEE Trans. Knowl. Data Eng., 2021)

Multi-View Clustering on Topological Manifold. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001; Quanhui Liu (AAAI, 2022)

DARER: Dual-task Temporal Relational Recurrent Reasoning Network for Joint Dialog Sentiment Classification and Act Recognition. - Bowen Xing; Ivor W. Tsang (ACL (Findings), 2022)

Co-guiding Net: Achieving Mutual Guidances between Multiple Intent Detection and Slot Filling via Heterogeneous Semantics-Label Graphs. - Bowen Xing; Ivor W. Tsang (EMNLP, 2022)

Group is better than individual: Exploiting Label Topologies and Label Relations for Joint Multiple Intent Detection and Slot Filling. - Bowen Xing; Ivor W. Tsang (EMNLP, 2022)

Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations. - Yan Zhang 036; Changyu Li; Ivor W. Tsang; Hui Xu; Lixin Duan; Hongzhi Yin; Wen Li 001; Jie Shao 001 (ICDE, 2022)

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

Learning Smooth Representation for Multi-view Subspace Clustering. - Shudong Huang; Yixi Liu; Yazhou Ren 001; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (ACM Multimedia, 2022)

Multi-view Subspace Clustering on Topological Manifold. - Shudong Huang; Hongjie Wu; Yazhou Ren 001; Ivor W. Tsang; Zenglin Xu; Wentao Feng; Jiancheng Lv 001 (NeurIPS, 2022)

Edge but not Least: Cross-View Graph Pooling. - Xiaowei Zhou 003; Jie Yin 001; Ivor W. Tsang (ECML/PKDD (2), 2022)

DigNet: Digging Clues from Local-Global Interactive Graph for Aspect-level Sentiment Classification. - Bowen Xing; Ivor W. Tsang (CoRR, 2022)

Latent Boundary-guided Adversarial Training. - Xiaowei Zhou 003; Ivor W. Tsang; Jie Yin 001 (CoRR, 2022)

When an Active Learner Meets a Black-box Teacher. - Xiaofeng Cao 002; Yaming Guo; Tieru Wu; Ivor W. Tsang (CoRR, 2022)

A Survey of Learning on Small Data. - Xiaofeng Cao 002; Weixin Bu; Shengjun Huang; Ying-Peng Tang; Yaming Guo; Yi Chang 001; Ivor W. Tsang (CoRR, 2022)

One-shot Machine Teaching: Cost Very Few Examples to Converge Faster. - Chen Zhang; Xiaofeng Cao 002; Yi Chang 001; Ivor W. Tsang (CoRR, 2022)

Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis. - Bowen Xing; Ivor W. Tsang (J. Artif. Intell. Res., 2022)

Fast and Robust Rank Aggregation against Model Misspecification. - Yuangang Pan; Ivor W. Tsang; Weijie Chen 001; Gang Niu 001; Masashi Sugiyama (J. Mach. Learn. Res., 2022)

XAI Beyond Classification: Interpretable Neural Clustering. - Xi Peng 001; Yunfan Li 003; Ivor W. Tsang; Hongyuan Zhu; Jiancheng Lv 001; Joey Tianyi Zhou (J. Mach. Learn. Res., 2022)

Multiple partitions alignment via spectral rotation. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (Mach. Learn., 2022)

Distribution Disagreement via Lorentzian Focal Representation. - Xiaofeng Cao 002; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Learning on Attribute-Missing Graphs. - Xu Chen 026; Siheng Chen; Jiangchao Yao; Huangjie Zheng; Ya Zhang 002; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

The Emerging Trends of Multi-Label Learning. - Weiwei Liu 003; Haobo Wang 001; Xiaobo Shen 001; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Recursive Copy and Paste GAN: Face Hallucination From Shaded Thumbnails. - Yang Zhang 067; Ivor W. Tsang; Yawei Luo; Changhui Hu 001; Xiaobo Lu; Xin Yu 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Efficient federated multi-view learning. - Shudong Huang; Wei Shi; Zenglin Xu; Ivor W. Tsang; Jiancheng Lv 001 (Pattern Recognit., 2022)

Cold-Start Active Sampling Via γ-Tube. - Xiaofeng Cao 002; Ivor W. Tsang; Jianliang Xu (IEEE Trans. Cybern., 2022)

Understand Me, if You Refer to Aspect Knowledge: Knowledge-Aware Gated Recurrent Memory Network. - Bowen Xing; Ivor W. Tsang (IEEE Trans. Emerg. Top. Comput. Intell., 2022)

Towards Faster Vehicle Routing by Transferring Knowledge From Customer Representation. - Liang Feng 001; Yuxiao Huang; Ivor W. Tsang; Abhishek Gupta 001; Ke Tang 001; Kay Chen Tan; Yew-Soon Ong (IEEE Trans. Intell. Transp. Syst., 2022)

Domain-Adversarial Network Alignment. - Huiting Hong; Xin Li 033; Yuangang Pan; Ivor W. Tsang (IEEE Trans. Knowl. Data Eng., 2022)

Measuring Diversity in Graph Learning: A Unified Framework for Structured Multi-View Clustering. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (IEEE Trans. Knowl. Data Eng., 2022)

Deep Pairwise Hashing for Cold-Start Recommendation. - Yan Zhang 036; Ivor W. Tsang; Hongzhi Yin; Guowu Yang; Defu Lian; Jingjing Li 001 (IEEE Trans. Knowl. Data Eng., 2022)

Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning. - Baijiong Lin; Feiyang Ye 001; Yu Zhang 006; Ivor W. Tsang (Trans. Mach. Learn. Res., 2022)

Deep Co-Image-Label Hashing for Multi-Label Image Retrieval. - Xiaobo Shen 001; Guohua Dong; Yuhui Zheng; Long Lan; Ivor W. Tsang; Quan-Sen Sun (IEEE Trans. Multim., 2022)

Shattering Distribution for Active Learning. - Xiaofeng Cao 002; Ivor W. Tsang (IEEE Trans. Neural Networks Learn. Syst., 2022)

Learning With Label Proportions by Incorporating Unmarked Data. - Jing Chai; Ivor W. Tsang (IEEE Trans. Neural Networks Learn. Syst., 2022)

MTKDN: Multi-Task Knowledge Disentanglement Network for Recommendation. - Haotian Wu 005; Bowen Xing; Ivor W. Tsang (CIKM, 2023)

Causal Intervention for Abstractive Related Work Generation. - Jiachang Liu 004; Qi Zhang 020; Chongyang Shi 001; Usman Naseem; Shoujin Wang; Liang Hu 004; Ivor W. Tsang (EMNLP (Findings), 2023)

Leveraging Inpainting for Single-Image Shadow Removal. - Xiaoguang Li; Qing Guo 005; Rabab Abdelfattah; Di Lin 002; Wei Feng 005; Ivor W. Tsang; Song Wang 002 (ICCV, 2023)

Nonparametric Iterative Machine Teaching. - Chen Zhang; Xiaofeng Cao 002; Weiyang Liu; Ivor W. Tsang; James T. Kwok (ICML, 2023)

Multi-Task Learning via Time-Aware Neural ODE. - Feiyang Ye 001; Xuehao Wang; Yu Zhang 006; Ivor W. Tsang (IJCAI, 2023)

Nonparametric Teaching for Multiple Learners. - Chen Zhang; Xiaofeng Cao 002; Weiyang Liu; Ivor W. Tsang; James T. Kwok (NeurIPS, 2023)

Co-Evolving Graph Reasoning Network for Emotion-Cause Pair Extraction. - Bowen Xing; Ivor W. Tsang (ECML/PKDD (1), 2023)

Adversary-Aware Partial label learning with Label distillation. - Cheng Chen; Yueming Lyu; Ivor W. Tsang (CoRR, 2023)

Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search. - Kim Yong Tan; Yueming Lyu; Yew Soon Ong; Ivor W. Tsang (CoRR, 2023)

UTSGAN: Unseen Transition Suss GAN for Transition-Aware Image-to-image Translation. - Yaxin Shi; Xiaowei Zhou 003; Ping Liu 004; Ivor W. Tsang (CoRR, 2023)

Learning Restoration is Not Enough: Transfering Identical Mapping for Single-Image Shadow Removal. - Xiaoguang Li; Qing Guo 005; Pingping Cai; Wei Feng 005; Ivor W. Tsang; Song Wang 002 (CoRR, 2023)

Learning Structured Components: Towards Modular and Interpretable Multivariate Time Series Forecasting. - Jinliang Deng; Xiusi Chen; Renhe Jiang; Du Yin; Yi Yang 001; Xuan Song 001; Ivor W. Tsang (CoRR, 2023)

Causal Intervention for Abstractive Related Work Generation. - Jiachang Liu 004; Qi Zhang 020; Chongyang Shi 001; Usman Naseem; Shoujin Wang; Ivor W. Tsang (CoRR, 2023)

On the Robustness of Segment Anything. - Yihao Huang 001; Yue Cao; Tianlin Li; Felix Juefei-Xu; Di Lin 002; Ivor W. Tsang; Yang Liu 003; Qing Guo 005 (CoRR, 2023)

SuperInpaint: Learning Detail-Enhanced Attentional Implicit Representation for Super-resolutional Image Inpainting. - Canyu Zhang; Qing Guo 005; Xiaoguang Li; Renjie Wan; Hongkai Yu; Ivor W. Tsang; Song Wang 002 (CoRR, 2023)

Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection. - Kairui Hu; Ming Yan 007; Joey Tianyi Zhou; Ivor W. Tsang; Wen Haw Chong; Yong Keong Yap (CoRR, 2023)

Aggregation Weighting of Federated Learning via Generalization Bound Estimation. - Mingwei Xu; Xiaofeng Cao 002; Ivor W. Tsang; James T. Kwok (CoRR, 2023)

Leveraging Open-Vocabulary Diffusion to Camouflaged Instance Segmentation. - Tuan-Anh Vu; Duc Thanh Nguyen; Qing Guo 005; Binh-Son Hua; Nhat Minh Chung; Ivor W. Tsang; Sai-Kit Yeung (CoRR, 2023)

Structure-Informed Shadow Removal Networks. - Yuhao Liu 001; Qing Guo 005; Lan Fu; Zhanghan Ke; Ke Xu 010; Wei Feng 005; Ivor W. Tsang; Rynson W. H. Lau (IEEE Trans. Image Process., 2023)

Contrastive Attraction and Contrastive Repulsion for Representation Learning. - Huangjie Zheng; Xu Chen 026; Jiangchao Yao; Hongxia Yang; Chunyuan Li; Ya Zhang 002; Hao Zhang 050; Ivor W. Tsang; Jingren Zhou 001; Mingyuan Zhou (Trans. Mach. Learn. Res., 2023)

Toward Equivalent Transformation of User Preferences in Cross Domain Recommendation. - Xu Chen 026; Ya Zhang 002; Ivor W. Tsang; Yuangang Pan; Jingchao Su (ACM Trans. Inf. Syst., 2023)

Open Set Domain Adaptation With Soft Unknown-Class Rejection. - Yiming Xu; Lin Chen 021; Lixin Duan; Ivor W. Tsang; Jiebo Luo 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Latent Representation Guided Multi-View Clustering. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (IEEE Trans. Knowl. Data Eng., 2023)

Latent Class-Conditional Noise Model. - Jiangchao Yao; Bo Han 003; Zhihan Zhou 002; Ya Zhang 002; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

A Multi-View Multi-Task Learning Framework for Multi-Variate Time Series Forecasting. - Jinliang Deng; Xiusi Chen; Renhe Jiang; Xuan Song 001; Ivor W. Tsang (IEEE Trans. Knowl. Data Eng., 2023)

Multi-View Subspace Clustering by Joint Measuring of Consistency and Diversity. - Shudong Huang; Yixi Liu; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (IEEE Trans. Knowl. Data Eng., 2023)

MetaCAR: Cross-Domain Meta-Augmentation for Content-Aware Recommendation. - Hui Xu; Changyu Li; Yan Zhang 036; Lixin Duan; Ivor W. Tsang; Jie Shao 001 (IEEE Trans. Knowl. Data Eng., 2023)

Missingness-Pattern-Adaptive Learning With Incomplete Data. - Yongshun Gong; Zhibin Li 002; Wei Liu 007; Xiankai Lu; Xinwang Liu 002; Ivor W. Tsang; Yilong Yin (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

LADDER: Latent boundary-guided adversarial training. - Xiaowei Zhou 003; Ivor W. Tsang; Jie Yin 001 (Mach. Learn., 2023)

Earning Extra Performance From Restrictive Feedbacks. - Jing Li 009; Yuangang Pan; Yueming Lyu; Yinghua Yao; Yulei Sui; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Data-Efficient Learning via Minimizing Hyperspherical Energy. - Xiaofeng Cao 002; Weiyang Liu; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

DifFormer: Multi-Resolutional Differencing Transformer With Dynamic Ranging for Time Series Analysis. - Bing Li 002; Wei Cui 002; Le Zhang 001; Ce Zhu; Wei Wang 011; Ivor W. Tsang; Joey Tianyi Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Noisy Label Learning With Provable Consistency for a Wider Family of Losses. - Defu Liu 001; Wen Li 001; Lixin Duan; Ivor W. Tsang; Guowu Yang (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Relational Temporal Graph Reasoning for Dual-Task Dialogue Language Understanding. - Bowen Xing; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

PC-X: Profound Clustering via Slow Exemplars. - Yuangang Pan; Yinghua Yao; Ivor W. Tsang (CPAL, 2024)

AHIVE: Anatomy-Aware Hierarchical Vision Encoding for Interactive Radiology Report Retrieval. - Sixing Yan; William K. Cheung 001; Ivor W. Tsang; Keith Chin; Terence M. Tong; Ka Chun Cheung; Simon See (CVPR, 2024)

A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. - Feiyang Ye 001; Baijiong Lin; Xiaofeng Cao 002; Yu Zhang 006; Ivor W. Tsang (ECAI, 2024)

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 005 (ECCV (57), 2024)

DC-Instruct: An Effective Framework for Generative Multi-intent Spoken Language Understanding. - Bowen Xing; Lizi Liao; Minlie Huang; Ivor W. Tsang (EMNLP, 2024)

Multisize Dataset Condensation. - Yang He 002; Lingao Xiao; Joey Tianyi Zhou; Ivor W. Tsang (ICLR, 2024)

On Harmonizing Implicit Subpopulations. - Feng Hong 004; Jiangchao Yao; Yueming Lyu; Zhihan Zhou 002; Ivor W. Tsang; Ya Zhang 002; Yanfeng Wang 001 (ICLR, 2024)

Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold. - Jun Chen 023; Haishan Ye; Mengmeng Wang 005; Tianxin Huang; Guang Dai; Ivor W. Tsang; Yong Liu 007 (ICLR, 2024)

IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks. - Yue Cao; Tianlin Li; Xiaofeng Cao 002; Ivor W. Tsang; Yang Liu 003; Qing Guo 005 (ICLR, 2024)

Self-Teaching Prompting for Multi-Intent Learning with Limited Supervision. - Cheng Chen; Ivor W. Tsang (Tiny Papers @ ICLR, 2024)

Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning. - Feiyang Ye 001; Yueming Lyu; Xuehao Wang; Yu Zhang 006; Ivor W. Tsang (ICLR, 2024)

Diversified Batch Selection for Training Acceleration. - Feng Hong 004; Yueming Lyu; Jiangchao Yao; Ya Zhang 002; Ivor W. Tsang; Yanfeng Wang 001 (ICML, 2024)

Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods. - Hao Di; Haishan Ye; Xiangyu Chang; Guang Dai; Ivor W. Tsang (ICML, 2024)

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 (ICML, 2024)

Can Gaussian Sketching Converge Faster on a Preconditioned Landscape? - Yilong Wang; Haishan Ye; Guang Dai; Ivor W. Tsang (ICML, 2024)

Fast Unpaired Multi-view Clustering. - Xingfeng Li 004; Yuangang Pan; Yinghui Sun; Quansen Sun; Ivor W. Tsang; Zhenwen Ren (IJCAI, 2024)

Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection. - Kairui Hu; Ming Yan 007; Wen Haw Chong; Yong Keong Yap; Cuntai Guan; Joey Tianyi Zhou; Ivor W. Tsang (IJCNN, 2024)

Cross-Context Backdoor Attacks against Graph Prompt Learning. - Xiaoting Lyu; Yufei Han 001; Wei Wang 012; Hangwei Qian; Ivor W. Tsang; Xiangliang Zhang 001 (KDD, 2024)

Diagnose with Uncertainty Awareness: Diagnostic Uncertainty Encoding Framework for Radiology Report Generation. - Sixing Yan; Haiyan Yin; Ivor W. Tsang; William K. Cheung 001 (UNSURE@MICCAI, 2024)

MetaRepair: Learning to Repair Deep Neural Networks from Repairing Experiences. - Yun Xing; Qing Guo 005; Xiaofeng Cao 002; Ivor W. Tsang; Lei Ma 003 (ACM Multimedia, 2024)

Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting. - Jinliang Deng; Feiyang Ye 001; Du Yin; Xuan Song 001; Ivor W. Tsang; Hui Xiong 001 (NeurIPS, 2024)

Towards Harmless Rawlsian Fairness Regardless of Demographic Prior. - Xuanqian Wang; Jing Li 009; Ivor W. Tsang; Yew Soon Ong (NeurIPS, 2024)

Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization. - Mingwei Xu; Xiaofeng Cao 002; Ivor W. Tsang (NeurIPS, 2024)

Low-Hanging Fruit: Knowledge Distillation from Noisy Teachers for Open Domain Spoken Language Understanding. - Cheng Chen; Bowen Xing; Ivor W. Tsang (ECML/PKDD (4), 2024)

Multi-objective meta-learning. - Feiyang Ye 001; Baijiong Lin; Zhixiong Yue; Yu Zhang 006; Ivor W. Tsang (Artif. Intell., 2024)

Collaborative Knowledge Infusion for Low-Resource Stance Detection. - Ming Yan 007; Joey Tianyi Zhou; Ivor W. Tsang (Big Data Min. Anal., 2024)

The Bigger the Better? Rethinking the Effective Model Scale in Long-term Time Series Forecasting. - Jinliang Deng; Xuan Song 001; Ivor W. Tsang; Hui Xiong 001 (CoRR, 2024)

HC2L: Hybrid and Cooperative Contrastive Learning for Cross-lingual Spoken Language Understanding. - Bowen Xing; Ivor W. Tsang (CoRR, 2024)

Covariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generation. - Yueming Lyu; Kim Yong Tan; Yew Soon Ong; Ivor W. Tsang (CoRR, 2024)

Quality Diversity Imitation Learning. - Zhenglin Wan; Xingrui Yu; David Mark Bossens; Yueming Lyu; Qing Guo 005; Flint Xiaofeng Fan; Ivor W. Tsang (CoRR, 2024)

Self-Assessed Generation: Trustworthy Label Generation for Optical Flow and Stereo Matching in Real-world. - Han Ling; Yinghui Sun; Quansen Sun; Ivor W. Tsang; Yuhui Zheng (CoRR, 2024)

ExpertFlow: Optimized Expert Activation and Token Allocation for Efficient Mixture-of-Experts Inference. - Xin He; Shunkang Zhang; Yuxin Wang 003; Haiyan Yin; Zihao Zeng; Shaohuai Shi; Zhenheng Tang; Xiaowen Chu 001; Ivor W. Tsang; Yew-Soon Ong (CoRR, 2024)

Semantic-Aligned Adversarial Evolution Triangle for High-Transferability Vision-Language Attack. - Xiaojun Jia; Sensen Gao; Qing Guo 005; Ke Ma 001; Yihao Huang 001; Simeng Qin; Yang Liu 003; Ivor W. Tsang; Xiaochun Cao (CoRR, 2024)

Alpha and Prejudice: Improving α-sized Worst-case Fairness via Intrinsic Reweighting. - Jing Li 009; Yinghua Yao; Yuangang Pan; Xuanqian Wang; Ivor W. Tsang; Xiuju Fu (CoRR, 2024)

Branches, Assemble! Multi-Branch Cooperation Network for Large-Scale Click-Through Rate Prediction at Taobao. - Xu Chen 026; Zida Cheng; Yuangang Pan; Shuai Xiao 002; Xiaoming Liu 011; Jinsong Lan; Qingwen Liu 002; Ivor W. Tsang (CoRR, 2024)

SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments. - Yue Cao; Yun Xing; Jie Zhang 002; Di Lin 002; Tianwei Zhang 004; Ivor W. Tsang; Yang Liu 003; Qing Guo 005 (CoRR, 2024)

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents. - Yun Xing; Nhat Chung; Jie Zhang 002; Yue Cao; Ivor W. Tsang; Yang Liu 003; Lei Ma 003; Qing Guo 005 (CoRR, 2024)

Exploiting Contextual Target Attributes for Target Sentiment Classification. - Bowen Xing; Ivor W. Tsang (J. Artif. Intell. Res., 2024)

USN: A Robust Imitation Learning Method against Diverse Action Noise. - Xingrui Yu; Bo Han 003; Ivor W. Tsang (J. Artif. Intell. Res., 2024)

Generative Adversarial Ranking Nets. - Yinghua Yao; Yuangang Pan; Jing Li 009; Ivor W. Tsang; Xin Yao 001 (J. Mach. Learn. Res., 2024)

Adversarial Learning for Coordinate Regression Through $k$k-Layer Penetrating Representation. - Mengxi Jiang; Yulei Sui; Yunqi Lei; Xiaofei Xie; Cuihua Li; Yang Liu 003; Ivor W. Tsang (IEEE Trans. Dependable Secur. Comput., 2024)

Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting. - Jinliang Deng; Xiusi Chen; Renhe Jiang; Du Yin; Yi Yang 001; Xuan Song 001; Ivor W. Tsang (IEEE Trans. Knowl. Data Eng., 2024)

BGAE: Auto-Encoding Multi-View Bipartite Graph Clustering. - Liang Li; Yuangang Pan; Jie Liu 002; Yue Liu 008; Xinwang Liu 002; Kenli Li 001; Ivor W. Tsang; Keqin Li 001 (IEEE Trans. Knowl. Data Eng., 2024)

Learning node representations against perturbations. - Xu Chen 026; Yuangang Pan; Ivor W. Tsang; Ya Zhang 002 (Pattern Recognit., 2024)

Enhancing Locally Adaptive Smoothing of Graph Neural Networks Via Laplacian Node Disagreement. - Yu Wang 152; Liang Hu 001; Xiaofeng Cao 002; Yi Chang 001; Ivor W. Tsang (IEEE Trans. Knowl. Data Eng., 2024)

CGDD: Multiview Graph Clustering via Cross-Graph Diversity Detection. - Shudong Huang; Ivor W. Tsang; Zenglin Xu; Jiancheng Lv 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Differential-Critic GAN: Generating What You Want by a Cue of Preferences. - Yinghua Yao; Yuangang Pan; Ivor W. Tsang; Xin Yao 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Online Multi-Agent Forecasting With Interpretable Collaborative Graph Neural Networks. - Maosen Li; Siheng Chen; Yanning Shen; Genjia Liu; Ivor W. Tsang; Ya Zhang 002 (IEEE Trans. Neural Networks Learn. Syst., 2024)

A Convergence Path to Deep Learning on Noisy Labels. - Defu Liu 001; Ivor W. Tsang; Guowu Yang (IEEE Trans. Neural Networks Learn. Syst., 2024)

Coarse-to-Fine Contrastive Learning on Graphs. - Peiyao Zhao; Yuangang Pan; Xin Li 033; Xu Chen 026; Ivor W. Tsang; Lejian Liao (IEEE Trans. Neural Networks Learn. Syst., 2024)

Co-Guiding for Multi-Intent Spoken Language Understanding. - Bowen Xing; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Imitation Learning: Progress, Taxonomies and Challenges. - Boyuan Zheng; Sunny Verma; Jianlong Zhou; Ivor W. Tsang; Fang Chen 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Sanitized clustering against confounding bias. - Yinghua Yao; Yuangang Pan; Jing Li 009; Ivor W. Tsang; Xin Yao 001 (Mach. Learn., 2024)

PROUD: PaRetO-gUided diffusion model for multi-objective generation. - Yinghua Yao; Yuangang Pan; Jing Li 009; Ivor W. Tsang; Xin Yao 001 (Mach. Learn., 2024)

Distribution Matching for Machine Teaching. - Xiaofeng Cao 002; Ivor W. Tsang (IEEE Trans. Neural Networks Learn. Syst., 2024)

Guest Editorial Special Issue on Resource Sustainable Computational and Artificial Intelligence. - Joey Tianyi Zhou; Ivor W. Tsang; Yew Soon Ong (IEEE Trans. Emerg. Top. Comput. Intell., 2024)

Taming Overconfident Prediction on Unlabeled Data From Hindsight. - Jing Li 009; Yuangang Pan; Ivor W. Tsang (IEEE Trans. Neural Networks Learn. Syst., 2024)

Transductive Reward Inference on Graph. - Bohao Qu; Xiaofeng Cao 002; Qing Guo 005; Yi Chang 001; Ivor W. Tsang; Chengqi Zhang (IEEE Trans. Knowl. Data Eng., 2024)

Diversifying Policies With Non-Markov Dispersion to Expand the Solution Space. - Bohao Qu; Xiaofeng Cao 002; Yi Chang 001; Ivor W. Tsang; Yew-Soon Ong (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

HC$^{2}$2L: Hybrid and Cooperative Contrastive Learning for Cross-Lingual Spoken Language Understanding. - Bowen Xing; Ivor W. Tsang (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Euclidean Distance is Not Your Swiss Army Knife. - Yuze Tan; Yixi Liu; Hongjie Wu; Shudong Huang; Zenglin Xu; Ivor W. Tsang; Jiancheng Lv 001 (IEEE Trans. Knowl. Data Eng., 2024)

Max-Mahalanobis Anchors Guidance for Multi-View Clustering. - Pei Zhang 008; Yuangang Pan; Siwei Wang 001; Shengju Yu; Huiying Xu; En Zhu; Xinwang Liu 002; Ivor W. Tsang (AAAI, 2025)

Boosting with Fewer Tokens: Multi-Query Optimization for LLMs Using Node Text and Neighbor Cues. - Yujie Fang; Xin Li 033; Yuangang Pan; Xin Huang; Ivor W. Tsang (ICDE, 2025)

BGAE: Auto-encoding Multi-view Bipartite Graph Clustering (Extended Abstract). - Liang Li; Yuangang Pan; Jie Liu 002; Yue Liu 008; Xinwang Liu 002; Kenli Li 001; Ivor W. Tsang; Keqin Li 001 (ICDE, 2025)

Sharpness-Aware Black-Box Optimization. - Feiyang Ye 001; Yueming Lyu; Xuehao Wang; Masashi Sugiyama; Yu Zhang 006; Ivor W. Tsang (ICLR, 2025)

Training-Free Dataset Pruning for Instance Segmentation. - Yalun Dai; Lingao Xiao; Ivor W. Tsang; Yang He 002 (ICLR, 2025)

ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs. - Hao Di; Tong He; Haishan Ye; Yinghui Huang 001; Xiangyu Chang; Guang Dai; Ivor W. Tsang (ICLR, 2025)

Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation. - Kim Yong Tan; Yueming Lyu; Ivor W. Tsang; Yew-Soon Ong (ICLR, 2025)

Second-Order Fine-Tuning without Pain for LLMs: A Hessian Informed Zeroth-Order Optimizer. - Yanjun Zhao; Sizhe Dang; Haishan Ye; Guang Dai; Yi Qian 004; Ivor W. Tsang (ICLR, 2025)

Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration. - Heyang Zhao; Xingrui Yu; David Mark Bossens; Ivor W. Tsang; Quanquan Gu (ICLR, 2025)

Imitation from Diverse Behaviors: Wasserstein Quality Diversity Imitation Learning with Single-Step Archive Exploration. - Xingrui Yu; Zhenglin Wan; David Mark Bossens; Yueming Lyu; Qing Guo 005; Ivor W. Tsang (AAMAS, 2025)

Scalable unpaired multi-view clustering with Bipartite Graph Matching. - Xingfeng Li 004; Yuangang Pan; Yuan Sun 016; Yinghui Sun; Quansen Sun; Zhenwen Ren; Ivor W. Tsang (Inf. Fusion, 2025)

Sharpening deep graph clustering via diverse bellwethers. - Peiyao Zhao; Xin Li 033; Yuangang Pan; Ivor W. Tsang; Mingzhong Wang; Lejian Liao (Knowl. Based Syst., 2025)

Graph Potential Field Neural Network for Massive Agents Group-wise Path Planning. - Yueming Lyu; Xiaowei Zhou 003; Xingrui Yu; Ivor W. Tsang (Trans. Mach. Learn. Res., 2025)

Incomplete Multi-View Clustering With Paired and Balanced Dynamic Anchor Learning. - Xingfeng Li 004; Yuangang Pan; Yuan Sun 016; Quansen Sun; Yinghui Sun; Ivor W. Tsang; Zhenwen Ren (IEEE Trans. Multim., 2025)

Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking. - Jun Chen 023; Lina Liu 010; Tianyi Zhu; Yong Liu 007; Guang Dai; Yunliang Jiang; Ivor W. Tsang (IEEE Trans. Signal Process., 2025)

Active Sampling for Node Attribute Completion on Graphs. - Benyuan Liu; Xu Chen 026; Yanfeng Wang 001; Ya Zhang 002; Zhi Cao; Ivor W. Tsang (CoRR, 2025)

Mastering Continual Reinforcement Learning through Fine-Grained Sparse Network Allocation and Dormant Neuron Exploration. - Chengqi Zheng; Haiyan Yin; Jianda Chen; Terence Ng; Yew-Soon Ong; Ivor W. Tsang (CoRR, 2025)

Balanced Image Stylization with Style Matching Score. - Yuxin Jiang; Liming Jiang 001; Shuai Yang 001; Jia-Wei Liu; Ivor W. Tsang; Mike Zheng Shou (CoRR, 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 (Mach. Learn., 2025)

Exploring the Effectiveness and Interpretability of Texts in LLM-based Time Series Models. - Zhengke Sun; Hangwei Qian; Ivor W. Tsang (CoRR, 2025)

Generation With Nuanced Changes: Continuous Image-to-Image Translation With Adversarial Preferences. - Yinghua Yao; Yuangang Pan; Ivor W. Tsang; Xin Yao 001 (IEEE Trans. Artif. Intell., 2025)

Instructing Text-to-Image Diffusion Models via Classifier-Guided Semantic Optimization. - Yuanyuan Chang; Yinghua Yao; Tao Qin; Mengmeng Wang 005; Ivor W. Tsang; Guang Dai (CoRR, 2025)

MermaidFlow: Redefining Agentic Workflow Generation via Safety-Constrained Evolutionary Programming. - Chengqi Zheng; Jianda Chen; Yueming Lyu; Wen Zheng Terence Ng; Haopeng Zhang 005; Yew-Soon Ong; Ivor W. Tsang; Haiyan Yin (CoRR, 2025)

Multi-Modal Dataset Distillation in the Wild. - Zhuohang Dang; Minnan Luo; Chengyou Jia; Hangwei Qian; Xiaojun Chang; Ivor W. Tsang (CoRR, 2025)

Privacy Leaks by Adversaries: Adversarial Iterations for Membership Inference Attack. - Jing Xue; Zhishen Sun; Haishan Ye; Luo Luo; Xiangyu Chang; Ivor W. Tsang; Guang Dai (CoRR, 2025)

FZOO: Fast Zeroth-Order Optimizer for Fine-Tuning Large Language Models towards Adam-Scale Speed. - Sizhe Dang; Yangyang Guo; Yanjun Zhao; Haishan Ye; Xiaodong Zheng; Guang Dai; Ivor W. Tsang (CoRR, 2025)

DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches. - Yun Xing; Yue Cao; Nhat Chung; Jie Zhang 002; Ivor W. Tsang; Ming-Ming Cheng; Yang Liu 003; Lei Ma 003; Qing Guo 005 (CoRR, 2025)

Why Settle for One? Text-to-ImageSet Generation and Evaluation. - Chengyou Jia; Xin Shen; Zhuohang Dang; Zhuohang Dang; Changliang Xia; Weijia Wu; Xinyu Zhang; Hangwei Qian; Ivor W. Tsang; Minnan Luo (CoRR, 2025)

Time-variant Image Inpainting via Interactive Distribution Transition Estimation. - Yun Xing; Qing Guo 005; Xiaohong Li 001; Yihao Huang 001; Xiaofeng Cao 002; Di Lin 002; Ivor W. Tsang; Lei Ma 003 (CoRR, 2025)

Group feature selection using non-class data. - Chunna Li 001; Yuangang Pan; Weijie Chen 001; Ivor W. Tsang; Yuanhai Shao 001 (Mach. Learn., 2025)

Coherence-guided Preference Disentanglement for Cross-domain Recommendations. - Zongyi Xiang; Yan Zhang 036; Lixin Duan; Hongzhi Yin; Ivor W. Tsang (ACM Trans. Inf. Syst., 2025)

Decouple before Align: Visual Disentanglement Enhances Prompt Tuning. - Fei Zhang 016; Tianfei Zhou; Jiangchao Yao; Ya Zhang 002; Ivor W. Tsang; Yanfeng Wang 001 (CoRR, 2025)

RouteMark: A Fingerprint for Intellectual Property Attribution in Routing-based Model Merging. - Xin He; Junxi Shen; Zhenheng Tang; Xiaowen Chu 001; Bo Li 001; Ivor W. Tsang; Yew-Soon Ong (CoRR, 2025)

FOCUS: Frequency-Optimized Conditioning of DiffUSion Models for mitigating catastrophic forgetting during Test-Time Adaptation. - Gabriel Tjio; Jie Zhang 002; Xulei Yang; Yun Xing; Nhat Chung; Xiaofeng Cao 002; Ivor W. Tsang; Chee Keong Kwoh; Qing Guo 005 (CoRR, 2025)

Implicit Multi-Behavior Generative Recommendation With Mixture of Quantization. - Yuze Tan; Yanjie Gou; Kouying Xue; Shudong Huang; Yi Hu; Ivor W. Tsang; Jiancheng Lv 001 (IEEE Trans. Knowl. Data Eng., 2025)

Uncover and unlearn nuisances: agnostic fully test-time adaptation. - Ponhvoan Srey; Yaxin Shi; Hangwei Qian; Jing Li 009; Ivor W. Tsang (Mach. Learn., 2025)

JetBGC: Joint Robust Embedding and Structural Fusion Bipartite Graph Clustering. - Liang Li; Yuangang Pan; Junpu Zhang; Pei Zhang 008; Jie Liu 002; Xinwang Liu 002; Kenli Li 001; Ivor W. Tsang; Keqin Li 001 (IEEE Trans. Knowl. Data Eng., 2025)