| 2024 | ICMLC | Research on Attention-Based Multigranular Remote Sensing Image Extreme Object Detection Algorithm. | Meng Li, Eric C. C. Tsang, Weihua Xu, Qiang He |
| 2024 | ICMLC | Feature Selection based on Variable Universe Rough Set. | Wanting Wang, Eric C. C. Tsang, Weihua Xu |
| 2024 | ICMLC | Label Distribution Learning Method Based on Deep Forest. | Rong-Rong Wang, Eric C. C. Tsang, Weihua Xu |
| 2024 | ICMLC | Multi-Label Classification with Weakly Labeled Data Based on Concept-Cognitive Learning. | Jiaming Wu, Eric C. C. Tsang, Cheng-Ling Zhang, Lanzhen Yang |
| 2024 | ICMLC | Counting Formal Concepts of A Random Formal Context. | Lanzhen Yang, Eric C. C. Tsang, Chengling Zhang, Jiaming Wu |
| 2024 | ICMLC | A Weighted Granular-Ball Rough Set: Model and Attribute Reduction. | Zhonghao Zhang, Jingjing Song, Huige Li, Eric C. C. Tsang |
| 2023 | ICMLC | Local Weighted Neighborhood Rough Sets for Weakly Labeled Data. | Yanting Guo, Meng Hu, Qiang Liu, Eric C. C. Tsang, Xizhao Wang |
| 2021 | ICMLC | Rule Acquisition Based on Multi-Level Cognitive Learning in Multi-Decision Data. | Bingjiao Fan, Guo-Cheng Li, Eric C. C. Tsang, Wentao Li |
| 2021 | ICMLC | An Improved ${k}$-Means Algorithm with Spatial Constraints for Image Segmentation. | Meng Hu, Eric C. C. Tsang, Yanting Guo, Qingshuo Zhang |
| 2021 | ICMLC | Double-Quantitative-Based Knowledge Reduction Approach to Inconsistency Information System. | Wentao Li, Shi-Qi Zeng, Tao Zhan, Bingjiao Fan, Eric C. C. Tsang |
| 2021 | ICMLC | An Object-Induced Fuzzy Three-Way Concept Lattice Analysis Based on Two Thresholds. | Lanzhen Yang, Eric C. C. Tsang, Xi-Zhao Wang |
| 2021 | ICMLC | Fuzzt Set-Based Kernel Extreme Learning Machine Autoencoder for Multi-Label Classification. | Qingshuo Zhang, Eric C. C. Tsang, Meng Hu, Qiang He, Degang Chen |
| 2021 | ICMLC | A Matrix-Based Granular Reduct Approach in Formal Contexts. | Cheng-Ling Zhang, Eric C. C. Tsang, Wei-Hua Xu, Yidong Lin |
| 2021 | ICMLC | Accelerator on Multi-Granularity Attribute Reduction for Continuous Parameters. | Da-Sheng Zhao, Jingjing Song, Tai-Hua Xu, Eric C. C. Tsang |
| 2020 | ICMLC | A Fast Reduction Algorithm with Attribute Pre-Sort Based on Neighborhood Rough Set. | Meng Hu, Eric C. C. Tsang, Yanting Guo, Weihua Xu, Degang Chen |
| 2020 | ICMLC | Supervised Neighborhood Based Ensemble Attribute Reduction. | Jingjing Song, Zehua Jiang, Huili Dou, Eric C. C. Tsang |
| 2018 | ICMLC | Logical Disjunction Double-Quantitative Fuzzy Rough Sets. | Yanting Guo, Eric C. C. Tsang, Weihua Xu, Degang Chen |
| 2017 | ICMLC | A weighted multi-granulation decision-theoretic approach to multi-source decision systems. | Yanting Guo, Eric C. C. Tsang, Weihua Xu |
| 2017 | ICMLC | Weights based ranked fuzzy rough reduction. | Eric C. C. Tsang, Xingqi Fan, Xuefeng Li, Suyun Zhao |
| 2016 | ICMLC | Minimum decision cost reduct for fuzzy decision-theoretic rough set model. | Jingjing Song, Eric C. C. Tsang, Degang Chen, Xibei Yang |
| 2016 | ICMLC | Random analysis of statistical rough set. | Eric C. C. Tsang, Suyun Zhao |
| 2016 | ICMLC | Neighborhood collaborative classifiers. | Suping Xu, Xibei Yang, Eric C. C. Tsang, Eric Appiah Mantey |
| 2015 | ICMLC | A method to fuzzy multi-objective problems under random environment. | Eric C. C. Tsang, Jing-Duo Jie, Chen-Xia Jin |
| 2015 | ICMLC | Basic properties of fuzzy approximation operators under consistent functions. | Eric C. C. Tsang, Changzhong Wang, Yang Du, Qiang He |
| 2015 | ICMLC | The comparative study of fuzzy rough reduction. | Eric C. C. Tsang, Suyun Zhao |
| 2014 | ICMLC | Face Recognition Using Genetic Algorithm. | Qin Qing, Eric C. C. Tsang |
| 2014 | ICMLC | Neighbourhood-assignment attribute reduction based on general binary relations. | Eric C. C. Tsang, Changzhong Wang, Du Yan, Jiaze Li |
| 2014 | ICMLC | A Fast Algorithm to Building a Fuzzy Rough Classifier. | Eric C. C. Tsang, Suyun Zhao |
| 2013 | ICMLC | Attribute reduction and attribute characteristics of formal contexts. | Eric C. C. Tsang, Ming-Wen Shao |
| 2013 | ICMLC | Generalized variable precision probabilistic rough set. | Eric C. C. Tsang, Bingzhen Sun |
| 2013 | ICMLC | The topological structure in parameterized rough sets. | Eric C. C. Tsang, Suyun Zhao |
| 2012 | ICMLC | An attribute reduction method based on core samples set. | Eric C. C. Tsang, Chen-Xia Jin, Degang Chen, Fa-Chao Li |
| 2012 | ICMLC | Variable precision rough fuzzy set model based on general relations. | Eric C. C. Tsang, Weimin Ma, Bingzhen Sun |
| 2012 | ICMLC | Attribute reduction based on interval valued fuzzy granules. | Eric C. C. Tsang, S. Y. Zhao |
| 2011 | ICMLC | A property of reductions in Fuzzy Variable Precision Rough Set model. | Eric C. C. Tsang, Suyun Zhao, Cai-Li Zhou |
| 2010 | ICMLC | Sample selection with rough set. | Degang Chen, Xiao Zhang, Eric C. C. Tsang, Yongping Yang |
| 2010 | ICMLC | On the fuzzy generalization of the Dempster-Shafer theory of evidence. | Eric C. C. Tsang, Degang Chen |
| 2007 | SMC | Neural network ensemble pruning using sensitivity measure in web applications. | Patrick P. K. Chan, Xiaoqin Zeng, Eric C. C. Tsang, Daniel S. Yeung, John W. T. Lee |
| 2007 | SMC | An approach of attributes reduction based on fuzzy TL rough sets. | Degang Chen, Eric C. C. Tsang, Suyun Zhao |
| 2006 | SMC | Bankruptcy Prediction Using Multiple Classifier System with Mutual Information Feature Grouping. | Aki P. F. Chan, Wing W. Y. Ng, Daniel S. Yeung, Eric C. C. Tsang, Michael Firth |
| 2006 | SMC | Structured Large Margin Machine Ensemble. | Patrick P. K. Chan, Defeng Wang, Eric C. C. Tsang, Daniel S. Yeung |
| 2006 | SMC | A Discussion of Attribute Reduction in Fuzzy Rough Sets Using Support Vector Machine. | Eric C. C. Tsang, Degang Chen, Suyun Zhao, Qiang He |
| 2005 | ICMLC | Empirical Study on Fusion Methods Using Ensemble of RBFNN for Network Intrusion Detection. | Aki P. F. Chan, Daniel S. Yeung, Eric C. C. Tsang, Wing W. Y. Ng |
| 2005 | ICMLC | On the Local Reduction of Information System. | Degang Chen, Eric C. C. Tsang |
| 2005 | ICMLC | Refinement of Fuzzy Production Rules by Using a Fuzzy-Neural Approach. | Dongmei Huang, Minghu Ha, Ya-min Li, Eric C. C. Tsang |
| 2005 | ICMLC | A Covariance Matrix Based Approach to Internet Anomaly Detection. | Shuyuan Jin, Daniel S. Yeung, Xizhao Wang, Eric C. C. Tsang |
| 2005 | ICMLC | Construction of High Precision RBFNN with Low False Alarm for Detecting Flooding Based Denial of Service Attacks Using Stochastic Sensitivity Measure. | Wing W. Y. Ng, Aki P. F. Chan, Daniel S. Yeung, Eric C. C. Tsang |
| 2005 | ICMLC | Learning from an Incomplete Information System with Continuous-Valued Attributes by a Rough Set Technique. | Eric C. C. Tsang, Suyun Zhao, Daniel S. Yeung, John W. T. Lee |
| 2005 | KES | Multiple Classifier System with Feature Grouping for Intrusion Detection: Mutual Information Approach. | Aki P. F. Chan, Wing W. Y. Ng, Daniel S. Yeung, Eric C. C. Tsang |
| 2005 | MICCAI | Support Vector Clustering for Brain Activation Detection. | Defeng Wang, Lin Shi, Daniel S. Yeung, Pheng-Ann Heng, Tien-Tsin Wong, Eric C. C. Tsang |
| 2005 | SMC | A feature space analysis for anomaly detection. | Shuyuan Jin, Daniel S. Yeung, Xizhao Wang, Eric C. C. Tsang |
| 2005 | SMC | Quantitative study on the generalization error of multiple classifier systems. | Wing W. Y. Ng, Aki P. F. Chan, Daniel S. Yeung, Eric C. C. Tsang |
| 2005 | SMC | On attributes reduction with fuzzy rough sets. | Gloria C. Y. Tsang, Degang Chen, Eric C. C. Tsang, John W. T. Lee, Daniel S. Yeung |
| 2005 | SMC | Stability Analysis of Discrete Hopfield Neural Networks With Delay and Its Application. | Eric C. C. Tsang, Aki P. F. Chan, Daniel S. Yeung, S. S. Qiu |
| 2003 | SMC | Selecting representative cases by generalization capability. | Eric C. C. Tsang, Xi-Zhao Wang |
| 2001 | IJCAI | A General Updating Rule for Discrete Hopfield-Type Neural Network with Delay. | Shenshan Qiu, Eric C. C. Tsang, Daniel S. Yeung, Xizhao Wang |
| 2001 | SMC | Learning weights of fuzzy production rules by a max-min neural network. | Eric C. C. Tsang, Daniel S. Yeung, Xi-Zhao Wang |
| 2000 | SMC | Stability of discrete Hopfield neural networks with time-delay. | Shenshan Qiu, Eric C. C. Tsang, Daniel S. Yeung |
| 2000 | SMC | Mining fuzzy association rules with weighted items. | Yue Joyce Shu, Eric C. C. Tsang, Daniel S. Yeung, Daming Shi |
| 2000 | SMC | Fuzzy weighted classification rules induction from data. | Eric C. C. Tsang, Hongbing Li, Daniel S. Yeung, John W. T. Lee |
| 2000 | SMC | Refinement of fuzzy production rules by neuro-fuzzy networks. | Eric C. C. Tsang, Shenshan Qiu, Daniel S. Yeung |
| 1998 | SMC | Evaluation of printed circuit board assembly manufacturing systems using fuzzy colored Petri nets. | Simon C. K. Shiu, Eric C. C. Tsang, Daniel S. Yeung, Martin B. Lam |
| 1998 | SMC | Refining local weights and certainty factors using a fuzzy neural network. | Eric C. C. Tsang, Daniel S. Yeung |
| 1998 | SMC | Refinement of knowledge representation parameters in fuzzy production rules by genetic algorithms. | Eric C. C. Tsang, Daniel S. Yeung, John W. T. Lee |
| 1997 | KES | Acquiring and tuning knowledge representation parameters of fuzzy production rules using fuzzy expert networks. | Eric C. C. Tsang, Daniel S. Yeung |