Improved fuzzy knowledge representation and rule evaluation using fuzzy petri nets and degree of subsethood. - Daniel S. Yeung; Eric C. C. Tsang (Int. J. Intell. Syst., 1994)

Acquiring and tuning knowledge representation parameters of fuzzy production rules using fuzzy expert networks. - Eric C. C. Tsang; Daniel S. Yeung (KES (2), 1997)

Weighted fuzzy production rules. - Daniel S. Yeung; Eric C. C. Tsang (Fuzzy Sets Syst., 1997)

A comparative study on similarity-based fuzzy reasoning methods. - Daniel S. Yeung; Eric C. C. Tsang (IEEE Trans. Syst. Man Cybern. Part B, 1997)

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 (SMC, 1998)

Refining local weights and certainty factors using a fuzzy neural network. - Eric C. C. Tsang; Daniel S. Yeung (SMC, 1998)

Refinement of knowledge representation parameters in fuzzy production rules by genetic algorithms. - Eric C. C. Tsang; Daniel S. Yeung; John W. T. Lee (SMC, 1998)

A multilevel weighted fuzzy reasoning algorithm for expert systems. - Daniel S. Yeung; Eric C. C. Tsang (IEEE Trans. Syst. Man Cybern. Part A, 1998)

Modelling flexible manufacturing systems using weighted Fuzzy Coloured Petri Nets. - Daniel S. Yeung; Simon C. K. Shiu; Eric C. C. Tsang (J. Intell. Fuzzy Syst., 1999)

Stability of discrete Hopfield neural networks with time-delay. - Shenshan Qiu; Eric C. C. Tsang; Daniel S. Yeung (SMC, 2000)

Mining fuzzy association rules with weighted items. - Yue Joyce Shu; Eric C. C. Tsang; Daniel S. Yeung; Daming Shi 001 (SMC, 2000)

Fuzzy weighted classification rules induction from data. - Eric C. C. Tsang; Hongbing Li; Daniel S. Yeung; John W. T. Lee (SMC, 2000)

Refinement of fuzzy production rules by neuro-fuzzy networks. - Eric C. C. Tsang; Shenshan Qiu; Daniel S. Yeung (SMC, 2000)

Improving learning accuracy of fuzzy decision trees by hybrid neural networks. - Eric C. C. Tsang; Xizhao Wang; Daniel S. Yeung (IEEE Trans. Fuzzy Syst., 2000)

A General Updating Rule for Discrete Hopfield-Type Neural Network with Delay. - Shenshan Qiu; Eric C. C. Tsang; Daniel S. Yeung; Xizhao Wang (IJCAI, 2001)

Learning weights of fuzzy production rules by a max-min neural network. - Eric C. C. Tsang; Daniel S. Yeung; Xi-Zhao Wang (SMC, 2001)

A General Updating Rule for Discrete Hopfield-Type Neural Network with Time-Delay and the Corresponding Search Algorithm. - Daniel S. Yeung; Shenshan Qiu; Eric C. C. Tsang; Xizhao Wang (Int. J. Comput. Intell. Appl., 2001)

A comparative study on heuristic algorithms for generating fuzzy decision trees. - Xizhao Wang; Daniel S. Yeung; Eric C. C. Tsang (IEEE Trans. Syst. Man Cybern. Part B, 2001)

Ordinal fuzzy sets. - John Wan Tung Lee; Daniel S. Yeung; Eric C. C. Tsang (IEEE Trans. Fuzzy Syst., 2002)

Tuning certainty factor and local weight of fuzzy production rules by using fuzzy neural network. - Eric C. C. Tsang; John W. T. Lee; Daniel S. Yeung (IEEE Trans. Syst. Man Cybern. Part B, 2002)

Selecting representative cases by generalization capability. - Eric C. C. Tsang; Xi-Zhao Wang (SMC, 2003)

An Approach To Natural Stroke Extraction For Off-Line Loosely-Constrained Handwritten Chinese Characters. - Daniel S. Yeung; Hank-Shun Fong; Eric C. C. Tsang; Wenhao Shu; Xiaolong Wang 001 (Int. J. Pattern Recognit. Artif. Intell., 2003)

OFFSS: optimal fuzzy-valued feature subset selection. - Eric C. C. Tsang; Daniel S. Yeung; Xizhao Wang (IEEE Trans. Fuzzy Syst., 2003)

Feature Selection For Chinese Character Recognition Based On Inductive Learning. - Guoliang Qian; Daniel S. Yeung; Eric C. C. Tsang; Wenhao Shu (Int. J. Pattern Recognit. Artif. Intell., 2004)

Refinement of generated fuzzy production rules by using a fuzzy neural network. - Eric C. C. Tsang; Daniel S. Yeung; John W. T. Lee; D. M. Huang; X. Z. Wang (IEEE Trans. Syst. Man Cybern. Part B, 2004)

Handling interaction in fuzzy production rule reasoning. - Daniel S. Yeung; Xizhao Wang; Eric C. C. Tsang (IEEE Trans. Syst. Man Cybern. Part B, 2004)

Gene Selection Through Sensitivity Analysis of Support Vector Machines. - Defeng Wang; Daniel S. Yeung; Eric C. C. Tsang; Lin Shi 001 (CompLife, 2005)

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 (ICMLC, 2005)

On the Local Reduction of Information System. - Degang Chen 002; Eric C. C. Tsang (ICMLC, 2005)

Refinement of Fuzzy Production Rules by Using a Fuzzy-Neural Approach. - Dongmei Huang; Minghu Ha 001; Ya-min Li; Eric C. C. Tsang (ICMLC, 2005)

A Covariance Matrix Based Approach to Internet Anomaly Detection. - Shuyuan Jin; Daniel S. Yeung; Xizhao Wang; Eric C. C. Tsang (ICMLC, 2005)

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 (ICMLC, 2005)

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 (ICMLC, 2005)

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 (KES (3), 2005)

Support Vector Clustering for Brain Activation Detection. - Defeng Wang; Lin Shi 001; Daniel S. Yeung; Pheng-Ann Heng; Tien-Tsin Wong; Eric C. C. Tsang (MICCAI, 2005)

A feature space analysis for anomaly detection. - Shuyuan Jin; Daniel S. Yeung; Xizhao Wang; Eric C. C. Tsang (SMC, 2005)

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 (SMC, 2005)

On attributes reduction with fuzzy rough sets. - Gloria C. Y. Tsang; Degang Chen 002; Eric C. C. Tsang; John W. T. Lee; Daniel S. Yeung (SMC, 2005)

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 (SMC, 2005)

Some notes on equivalent fuzzy sets and fuzzy subgroups. - Degang Chen 002; Jiashang Jiang; Congxin Wu; Eric C. C. Tsang (Fuzzy Sets Syst., 2005)

An Approach To Case-Based Maintenance: Selecting Representative Cases. - Eric C. C. Tsang; Xizhao Wang (Int. J. Pattern Recognit. Artif. Intell., 2005)

Hierarchical clustering based on ordinal consistency. - John W. T. Lee; Daniel S. Yeung; Eric C. C. Tsang (Pattern Recognit., 2005)

On the generalization of fuzzy rough sets. - Daniel S. Yeung; Degang Chen 002; Eric C. C. Tsang; John W. T. Lee; Xizhao Wang (IEEE Trans. Fuzzy Syst., 2005)

General multifractional Fourier transform method based on the generalized permutation matrix group. - Qiwen Ran; Daniel S. Yeung; Eric C. C. Tsang; Qi Wang (IEEE Trans. Signal Process., 2005)

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 (SMC, 2006)

Structured Large Margin Machine Ensemble. - Patrick P. K. Chan; Defeng Wang; Eric C. C. Tsang; Daniel S. Yeung (SMC, 2006)

A Discussion of Attribute Reduction in Fuzzy Rough Sets Using Support Vector Machine. - Eric C. C. Tsang; Degang Chen 002; Suyun Zhao; Qiang He 003 (SMC, 2006)

Rough approximations on a complete completely distributive lattice with applications to generalized rough sets. - Degang Chen 002; Wenxiu Zhang; Daniel S. Yeung; Eric C. C. Tsang (Inf. Sci., 2006)

Rough sets and ordinal reducts. - John W. T. Lee; Daniel S. Yeung; Eric C. C. Tsang (Soft Comput., 2006)

Preface for the special issue: soft computing in machine learning and cybernetics in the journal Soft Computing. - Zhi-Qiang Liu; Daniel S. Yeung; Xizhao Wang; Eric C. C. Tsang; John W. T. Lee (Soft Comput., 2006)

Structured One-Class Classification. - Defeng Wang; Daniel S. Yeung; Eric C. C. Tsang (IEEE Trans. Syst. Man Cybern. Part B, 2006)

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 (SMC, 2007)

An approach of attributes reduction based on fuzzy TL rough sets. - Degang Chen 002; Eric C. C. Tsang; Suyun Zhao (SMC, 2007)

Sample Reduction for SVMs via Data Structure Analysis. - Defeng Wang; Daniel S. Yeung; Eric C. C. Tsang (SoSE, 2007)

Stability analysis of a discrete Hopfield neural network with delay. - Eric C. C. Tsang; S. S. Qiu; Daniel S. Yeung (Neurocomputing, 2007)

Convergence Analysis of a Discrete Hopfield Neural Network with Delay and its Application to Knowledge Refinement. - Eric C. C. Tsang; S. S. Qiu; Daniel S. Yeung (Int. J. Pattern Recognit. Artif. Intell., 2007)

Learning fuzzy rules from fuzzy samples based on rough set technique. - Xizhao Wang; Eric C. C. Tsang; Suyun Zhao; Degang Chen 002; Daniel S. Yeung (Inf. Sci., 2007)

Structured large margin machines: sensitive to data distributions. - Daniel S. Yeung; Defeng Wang; Wing W. Y. Ng; Eric C. C. Tsang; Xizhao Wang (Mach. Learn., 2007)

Ellipsoidal support vector clustering for functional MRI analysis. - Defeng Wang; Lin Shi 001; Daniel S. Yeung; Eric C. C. Tsang; Pheng-Ann Heng (Pattern Recognit., 2007)

Localized Generalization Error of Gaussian-based Classifiers and Visualization of Decision Boundaries. - Wing W. Y. Ng; Daniel S. Yeung; Defeng Wang; Eric C. C. Tsang; Xizhao Wang (Soft Comput., 2007)

Weighted Mahalanobis Distance Kernels for Support Vector Machines. - Defeng Wang; Daniel S. Yeung; Eric C. C. Tsang (IEEE Trans. Neural Networks, 2007)

Localized Generalization Error Model and Its Application to Architecture Selection for Radial Basis Function Neural Network. - Daniel S. Yeung; Wing W. Y. Ng; Defeng Wang; Eric C. C. Tsang; Xizhao Wang (IEEE Trans. Neural Networks, 2007)

Approximations and reducts with covering generalized rough sets. - Eric C. C. Tsang; Degang Chen 002; Daniel S. Yeung (Comput. Math. Appl., 2008)

A Novel Feature Grouping Method for Ensemble Neural Network Using Localized Generalization Error Model. - Aki P. F. Chan; Patrick P. K. Chan; Wing W. Y. Ng; Eric C. C. Tsang; Daniel S. Yeung (Int. J. Pattern Recognit. Artif. Intell., 2008)

The Localized Generalization Error Model for Single Layer Perceptron Neural Network and Sigmoid Support Vector Machine. - Wing W. Y. Ng; Daniel S. Yeung; Eric C. C. Tsang (Int. J. Pattern Recognit. Artif. Intell., 2008)

On fuzzy approximation operators in attribute reduction with fuzzy rough sets. - Suyun Zhao; Eric C. C. Tsang (Inf. Sci., 2008)

Feature selection using localized generalization error for supervised classification problems using RBFNN. - Wing W. Y. Ng; Daniel S. Yeung; Michael Firth; Eric C. C. Tsang; Xizhao Wang (Pattern Recognit., 2008)

Attributes Reduction Using Fuzzy Rough Sets. - Eric C. C. Tsang; Degang Chen 002; Daniel S. Yeung; Xizhao Wang; John W. T. Lee (IEEE Trans. Fuzzy Syst., 2008)

Nesting One-Against-One Algorithm Based on SVMs for Pattern Classification. - Bo Liu 002; Zhifeng Hao; Eric C. C. Tsang (IEEE Trans. Neural Networks, 2008)

Hybridization of Fuzzy and Rough Sets: Present and Future. - Eric C. C. Tsang; Qingcai Chen; Suyun Zhao; Daniel S. Yeung; Xizhao Wang (Fuzzy Sets and Their Extensions: Representation, Aggregation and Models, 2008)

The Model of Fuzzy Variable Precision Rough Sets. - Suyun Zhao; Eric C. C. Tsang; Degang Chen 002 (IEEE Trans. Fuzzy Syst., 2009)

Sample selection with rough set. - Degang Chen 002; Xiao Zhang 012; Eric C. C. Tsang; Yongping Yang (ICMLC, 2010)

On the fuzzy generalization of the Dempster-Shafer theory of evidence. - Eric C. C. Tsang; Degang Chen 002 (ICMLC, 2010)

Building a Rule-Based Classifier—A Fuzzy-Rough Set Approach. - Suyun Zhao; Eric C. C. Tsang; Degang Chen 002; Xizhao Wang (IEEE Trans. Knowl. Data Eng., 2010)

Decision Table Reduction in KDD: Fuzzy Rough Based Approach. - Eric C. C. Tsang; Suyun Zhao (Trans. Rough Sets, 2010)

A property of reductions in Fuzzy Variable Precision Rough Set model. - Eric C. C. Tsang; Suyun Zhao; Cai-Li Zhou (ICMLC, 2011)

An attribute reduction method based on core samples set. - Eric C. C. Tsang; Chen-Xia Jin; Degang Chen 002; Fa-Chao Li 001 (ICMLC, 2012)

Variable precision rough fuzzy set model based on general relations. - Eric C. C. Tsang; Weimin Ma; Bingzhen Sun (ICMLC, 2012)

Attribute reduction based on interval valued fuzzy granules. - Eric C. C. Tsang; S. Y. Zhao (ICMLC, 2012)

Attribute reduction and attribute characteristics of formal contexts. - Eric C. C. Tsang; Ming-Wen Shao (ICMLC, 2013)

Generalized variable precision probabilistic rough set. - Eric C. C. Tsang; Bingzhen Sun (ICMLC, 2013)

The topological structure in parameterized rough sets. - Eric C. C. Tsang; Suyun Zhao (ICMLC, 2013)

Nested structure in parameterized rough reduction. - Suyun Zhao; Xizhao Wang; Degang Chen 002; Eric C. C. Tsang (Inf. Sci., 2013)

Communication Between Information Systems Using Fuzzy Rough Sets. - Eric C. C. Tsang; Changzhong Wang; Degang Chen 002; Congxin Wu; Qinghua Hu (IEEE Trans. Fuzzy Syst., 2013)

Face Recognition Using Genetic Algorithm. - Qin Qing; Eric C. C. Tsang (ICMLC (CCIS volume), 2014)

Neighbourhood-assignment attribute reduction based on general binary relations. - Eric C. C. Tsang; Changzhong Wang; Du Yan; Jiaze Li (ICMLC, 2014)

A Fast Algorithm to Building a Fuzzy Rough Classifier. - Eric C. C. Tsang; Suyun Zhao (ICMLC (CCIS volume), 2014)

A method to fuzzy multi-objective problems under random environment. - Eric C. C. Tsang; Jing-Duo Jie; Chen-Xia Jin (ICMLC, 2015)

Basic properties of fuzzy approximation operators under consistent functions. - Eric C. C. Tsang; Changzhong Wang; Yang Du; Qiang He (ICMLC, 2015)

The comparative study of fuzzy rough reduction. - Eric C. C. Tsang; Suyun Zhao (ICMLC, 2015)

Minimum decision cost reduct for fuzzy decision-theoretic rough set model. - Jingjing Song; Eric C. C. Tsang; Degang Chen 002; Xibei Yang (ICMLC, 2016)

Random analysis of statistical rough set. - Eric C. C. Tsang; Su-Yun Zhao (ICMLC, 2016)

Neighborhood collaborative classifiers. - Suping Xu; Xibei Yang; Eric C. C. Tsang; Eric Appiah Mantey (ICMLC, 2016)

Multi-label learning with label-specific feature reduction. - Suping Xu; Xibei Yang; Hualong Yu; Dong-Jun Yu; Jingyu Yang 001; Eric C. C. Tsang (Knowl. Based Syst., 2016)

Feature and instance reduction for PNN classifiers based on fuzzy rough sets. - Eric C. C. Tsang; Qinghua Hu; Degang Chen 002 (Int. J. Mach. Learn. Cybern., 2016)

Data-Distribution-Aware Fuzzy Rough Set Model and its Application to Robust Classification. - Shuang An; Qinghua Hu; Witold Pedrycz; Pengfei Zhu 001; Eric C. C. Tsang (IEEE Trans. Cybern., 2016)

A weighted multi-granulation decision-theoretic approach to multi-source decision systems. - Yanting Guo; Eric C. C. Tsang; Weihua Xu 003 (ICMLC, 2017)

Weights based ranked fuzzy rough reduction. - Eric C. C. Tsang; Fan Xingqi; Xuefeng Li; Suyun Zhao (ICMLC, 2017)

A new compound arithmetic crossover-based genetic algorithm for constrained optimisation in enterprise systems. - Chenxia Jin; Fachao Li 001; Eric C. C. Tsang; Larissa Bulysheva; Mikhail Yu. Kataev (Enterp. Inf. Syst., 2017)

Fuzzy rough set based incremental attribute reduction from dynamic data with sample arriving. - Yanyan Yang 001; Degang Chen 002; Hui Wang 001; Eric C. C. Tsang; Deli Zhang (Fuzzy Sets Syst., 2017)

Discrete differential evolutions for the discounted {0-1} knapsack problem. - Hong Zhu 011; Yi-Chao He; Xizhao Wang; Eric C. C. Tsang (Int. J. Bio Inspired Comput., 2017)

Sensitivity based robust learning for stacked autoencoder against evasion attack. - Patrick P. K. Chan; Zhe Lin; Xian Hu; Eric C. C. Tsang; Daniel S. Yeung (Neurocomputing, 2017)

Monotonic classification extreme learning machine. - Hong Zhu 011; Eric C. C. Tsang; Xi-Zhao Wang; Rana Aamir Raza Ashfaq (Neurocomputing, 2017)

Double-quantitative rough fuzzy set based decisions: A logical operations method. - Bingjiao Fan; Eric C. C. Tsang; Weihua Xu 003; Jianhang Yu (Inf. Sci., 2017)

Optimal scale selection in dynamic multi-scale decision tables based on sequential three-way decisions. - Chen Hao; Jinhai Li; Min Fan; Wenqi Liu; Eric C. C. Tsang (Inf. Sci., 2017)

Generalized dominance rough set models for the dominance intuitionistic fuzzy information systems. - Xiaoxia Zhang; Degang Chen 002; Eric C. C. Tsang (Inf. Sci., 2017)

Minimal decision cost reduct in fuzzy decision-theoretic rough set model. - Jingjing Song; Eric C. C. Tsang; Degang Chen 002; Xibei Yang (Knowl. Based Syst., 2017)

General relation-based variable precision rough fuzzy set. - Eric C. C. Tsang; Bingzhen Sun; Weimin Ma (Int. J. Mach. Learn. Cybern., 2017)

Logical Disjunction Double-Quantitative Fuzzy Rough Sets. - Yanting Guo; Eric C. C. Tsang; Weihua Xu 003; Degang Chen 002 (ICMLC, 2018)

Training an extreme learning machine by localized generalization error model. - Hong Zhu 011; Eric C. C. Tsang; Jie Zhu (Soft Comput., 2018)

Local logical disjunction double-quantitative rough sets. - Yanting Guo; Eric C. C. Tsang; Weihua Xu 003; Degang Chen 002 (Inf. Sci., 2019)

Attribute-oriented cognitive concept learning strategy: a multi-level method. - Bingjiao Fan; Eric C. C. Tsang; Weihua Xu 003; Degang Chen 002; Wentao Li 004 (Int. J. Mach. Learn. Cybern., 2019)

Order based hierarchies on hesitant fuzzy approximation space. - Eric C. C. Tsang; Jingjing Song; Degang Chen 002; Xibei Yang (Int. J. Mach. Learn. Cybern., 2019)

A Fast Reduction Algorithm with Attribute Pre-Sort Based on Neighborhood Rough Set. - Meng Hu; Eric C. C. Tsang; Yanting Guo; Weihua Xu 003; Degang Chen 002 (ICMLC, 2020)

Supervised Neighborhood Based Ensemble Attribute Reduction. - Jingjing Song; Zehua Jiang; Huili Dou; Eric C. C. Tsang (ICMLC, 2020)

Incremental feature selection based on fuzzy rough sets. - Peng Ni; Suyun Zhao; Xizhao Wang; Hong Chen 001; Cuiping Li 001; Eric C. C. Tsang (Inf. Sci., 2020)

Incremental updating approximations for double-quantitative decision-theoretic rough sets with the variation of objects. - Yanting Guo; Eric C. C. Tsang; Meng Hu; Xuxin Lin; Degang Chen 002; Weihua Xu 003; Binbin Sang (Knowl. Based Syst., 2020)

Adaptive weighted generalized multi-granulation interval-valued decision-theoretic rough sets. - Yanting Guo; Eric C. C. Tsang; Weihua Xu 003; Degang Chen 002 (Knowl. Based Syst., 2020)

Multi-level cognitive concept learning method oriented to data sets with fuzziness: a perspective from features. - Eric C. C. Tsang; Bingjiao Fan; Degang Chen 002; Weihua Xu 003; Wentao Li 004 (Soft Comput., 2020)

Rule Acquisition Based on Multi-Level Cognitive Learning in Multi-Decision Data. - Bingjiao Fan; Guo-Cheng Li; Eric C. C. Tsang; Wentao Li 004 (ICMLC, 2021)

An Improved ${k}$-Means Algorithm with Spatial Constraints for Image Segmentation. - Meng Hu; Eric C. C. Tsang; Yanting Guo; Qingshuo Zhang (ICMLC, 2021)

Double-Quantitative-Based Knowledge Reduction Approach to Inconsistency Information System. - Wentao Li 004; Shi-Qi Zeng; Tao Zhan; Bingjiao Fan; Eric C. C. Tsang (ICMLC, 2021)

An Object-Induced Fuzzy Three-Way Concept Lattice Analysis Based on Two Thresholds. - Lanzhen Yang; Eric C. C. Tsang; Xi-Zhao Wang (ICMLC, 2021)

Fuzzt Set-Based Kernel Extreme Learning Machine Autoencoder for Multi-Label Classification. - Qingshuo Zhang; Eric C. C. Tsang; Meng Hu; Qiang He 003; Degang Chen 002 (ICMLC, 2021)

A Matrix-Based Granular Reduct Approach in Formal Contexts. - Cheng-Ling Zhang; Eric C. C. Tsang; Wei-Hua Xu 003; Yidong Lin (ICMLC, 2021)

Accelerator on Multi-Granularity Attribute Reduction for Continuous Parameters. - Da-Sheng Zhao; Jingjing Song; Tai-Hua Xu; Eric C. C. Tsang (ICMLC, 2021)

Robustness analysis of classical and fuzzy decision trees under adversarial evasion attack. - Patrick P. K. Chan; Juan Zheng; Han Liu 002; Eric C. C. Tsang; Daniel S. Yeung (Appl. Soft Comput., 2021)

A novel approach to attribute reduction based on weighted neighborhood rough sets. - Meng Hu; Eric C. C. Tsang; Yanting Guo; Degang Chen 002; Weihua Xu 003 (Knowl. Based Syst., 2021)

Causative label flip attack detection with data complexity measures. - Patrick P. K. Chan; Zhi-Min He; Xian Hu; Eric C. C. Tsang; Daniel S. Yeung; Wing W. Y. Ng (Int. J. Mach. Learn. Cybern., 2021)

Attribute reduction based on overlap degree and k-nearest-neighbor rough sets in decision information systems. - Meng Hu; Eric C. C. Tsang; Yanting Guo; Degang Chen 002; Weihua Xu 003 (Inf. Sci., 2022)

A robust approach to attribute reduction based on double fuzzy consistency measure. - Yanting Guo; Meng Hu; Xizhao Wang; Eric C. C. Tsang; Degang Chen 002; Weihua Xu 003 (Knowl. Based Syst., 2022)

A novel approach to concept-cognitive learning in interval-valued formal contexts: a granular computing viewpoint. - Meng Hu; Eric C. C. Tsang; Yanting Guo; Qingshuo Zhang; Degang Chen 002; Weihua Xu 003 (Int. J. Mach. Learn. Cybern., 2022)

Fast and Robust Attribute Reduction Based on the Separability in Fuzzy Decision Systems. - Meng Hu; Eric C. C. Tsang; Yanting Guo; Weihua Xu 003 (IEEE Trans. Cybern., 2022)

Local Weighted Neighborhood Rough Sets for Weakly Labeled Data. - Yanting Guo; Meng Hu; Qiang Liu; Eric C. C. Tsang; Xizhao Wang (ICMLC, 2023)

Attribute reduction based on neighborhood constrained fuzzy rough sets. - Meng Hu; Yanting Guo; Degang Chen 002; Eric C. C. Tsang; Qingshuo Zhang (Knowl. Based Syst., 2023)

Incremental concept-cognitive learning approach for concept classification oriented to weighted fuzzy concepts. - Cheng-Ling Zhang; Eric C. C. Tsang; Weihua Xu 003; Yidong Lin; Lanzhen Yang (Knowl. Based Syst., 2023)

Distance metric learning with local multiple kernel embedding. - Qingshuo Zhang; Eric C. C. Tsang; Qiang He 003; Meng Hu (Int. J. Mach. Learn. Cybern., 2023)

Ensemble of kernel extreme learning machine based elimination optimization for multi-label classification. - Qingshuo Zhang; Eric C. C. Tsang; Qiang He; Yanting Guo (Knowl. Based Syst., 2023)

ELM parameter estimation in view of maximum likelihood. - Lanzhen Yang; Eric C. C. Tsang; Xizhao Wang; Chengling Zhang (Neurocomputing, 2023)

Correlation concept-cognitive learning model for multi-label classification. - Jiaming Wu; Eric C. C. Tsang; Weihua Xu 003; Chengling Zhang; Lanzhen Yang (Knowl. Based Syst., 2024)

Dynamic updating variable precision three-way concept method based on two-way concept-cognitive learning in fuzzy formal contexts. - Chengling Zhang; Eric C. C. Tsang; Weihua Xu 003; Yidong Lin; Lanzhen Yang; Jiaming Wu (Inf. Sci., 2024)