Eric C. C. Tsang

According to our database, Eric C. C. Tsang authored at least 141 papers between 1994 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

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, Yidong Lin, Lanzhen Yang, Jiaming Wu

Inf. Sci., January, 2024

Correlation concept-cognitive learning model for multi-label classification.

Jiaming Wu, Eric C. C. Tsang, Weihua Xu, Chengling Zhang, Lanzhen Yang

Knowl. Based Syst., 2024

2023

ELM parameter estimation in view of maximum likelihood.

Lanzhen Yang, Eric C. C. Tsang, Xizhao Wang, Chengling Zhang

Neurocomputing, November, 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., October, 2023

Distance metric learning with local multiple kernel embedding.

Qingshuo Zhang, Eric C. C. Tsang, Qiang He, Meng Hu

Int. J. Mach. Learn. Cybern., January, 2023

Incremental concept-cognitive learning approach for concept classification oriented to weighted fuzzy concepts.

Cheng-Ling Zhang, Eric C. C. Tsang, Weihua Xu, Yidong Lin, Lanzhen Yang

Knowl. Based Syst., 2023

Attribute reduction based on neighborhood constrained fuzzy rough sets.

Meng Hu, Yanting Guo, Degang Chen, Eric C. C. Tsang, Qingshuo Zhang

Knowl. Based Syst., 2023

Local Weighted Neighborhood Rough Sets for Weakly Labeled Data.

Yanting Guo, Meng Hu, Qiang Liu, Eric C. C. Tsang, Xizhao Wang

Proceedings of the International Conference on Machine Learning and Cybernetics, 2023

2022

Fast and Robust Attribute Reduction Based on the Separability in Fuzzy Decision Systems.

Meng Hu, Eric C. C. Tsang, Yanting Guo, Weihua Xu

IEEE Trans. Cybern., 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, Weihua Xu

Int. J. Mach. Learn. Cybern., 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, Weihua Xu

Knowl. Based Syst., 2022

Attribute reduction based on overlap degree and <i>k</i>-nearest-neighbor rough sets in decision information systems.

Meng Hu, Eric C. C. Tsang, Yanting Guo, Degang Chen, Weihua Xu

Inf. Sci., 2022

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

A novel approach to attribute reduction based on weighted neighborhood rough sets.

Meng Hu, Eric C. C. Tsang, Yanting Guo, Degang Chen, Weihua Xu

Knowl. Based Syst., 2021

Robustness analysis of classical and fuzzy decision trees under adversarial evasion attack.

Patrick P. K. Chan, Juan Zheng, Han Liu, Eric C. C. Tsang, Daniel S. Yeung

Appl. Soft Comput., 2021

Accelerator on Multi-Granularity Attribute Reduction for Continuous Parameters.

Da-Sheng Zhao, Jingjing Song, Tai-Hua Xu, Eric C. C. Tsang

Proceedings of the International Conference on Machine Learning and Cybernetics, 2021

A Matrix-Based Granular Reduct Approach in Formal Contexts.

Cheng-Ling Zhang, Eric C. C. Tsang, Wei-Hua Xu, Yidong Lin

Proceedings of the International Conference on Machine Learning and Cybernetics, 2021

Fuzzt Set-Based Kernel Extreme Learning Machine Autoencoder for Multi-Label Classification.

Qingshuo Zhang, Eric C. C. Tsang, Meng Hu, Qiang He, Degang Chen

Proceedings of the International Conference on Machine Learning and Cybernetics, 2021

An Object-Induced Fuzzy Three-Way Concept Lattice Analysis Based on Two Thresholds.

Lanzhen Yang, Eric C. C. Tsang, Xi-Zhao Wang

Proceedings of the International Conference on Machine Learning and Cybernetics, 2021

Double-Quantitative-Based Knowledge Reduction Approach to Inconsistency Information System.

Wentao Li, Shi-Qi Zeng, Tao Zhan, Bingjiao Fan, Eric C. C. Tsang

Proceedings of the International Conference on Machine Learning and Cybernetics, 2021

An Improved ${k}$-Means Algorithm with Spatial Constraints for Image Segmentation.

Meng Hu, Eric C. C. Tsang, Yanting Guo, Qingshuo Zhang

Proceedings of the International Conference on Machine Learning and Cybernetics, 2021

Rule Acquisition Based on Multi-Level Cognitive Learning in Multi-Decision Data.

Bingjiao Fan, Guo-Cheng Li, Eric C. C. Tsang, Wentao Li

Proceedings of the International Conference on Machine Learning and Cybernetics, 2021

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, Weihua Xu, Wentao Li

Soft Comput., 2020

Adaptive weighted generalized multi-granulation interval-valued decision-theoretic rough sets.

Yanting Guo, Eric C. C. Tsang, Weihua Xu, Degang Chen

Knowl. Based Syst., 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, Weihua Xu, Binbin Sang

Knowl. Based Syst., 2020

Incremental feature selection based on fuzzy rough sets.

Peng Ni, Suyun Zhao, Xizhao Wang, Hong Chen, Cuiping Li, Eric C. C. Tsang

Inf. Sci., 2020

Supervised Neighborhood Based Ensemble Attribute Reduction.

Jingjing Song, Zehua Jiang, Huili Dou, Eric C. C. Tsang

Proceedings of the International Conference on Machine Learning and Cybernetics, 2020

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

Proceedings of the International Conference on Machine Learning and Cybernetics, 2020

2019

Order based hierarchies on hesitant fuzzy approximation space.

Eric C. C. Tsang, Jingjing Song, Degang Chen, Xibei Yang

Int. J. Mach. Learn. Cybern., 2019

Attribute-oriented cognitive concept learning strategy: a multi-level method.

Bingjiao Fan, Eric C. C. Tsang, Weihua Xu, Degang Chen, Wentao Li

Int. J. Mach. Learn. Cybern., 2019

Local logical disjunction double-quantitative rough sets.

Yanting Guo, Eric C. C. Tsang, Weihua Xu, Degang Chen

Inf. Sci., 2019

2018

Training an extreme learning machine by localized generalization error model.

Hong Zhu, Eric C. C. Tsang, Jie Zhu

Soft Comput., 2018

Logical Disjunction Double-Quantitative Fuzzy Rough Sets.

Yanting Guo, Eric C. C. Tsang, Weihua Xu, Degang Chen

Proceedings of the 2018 International Conference on Machine Learning and Cybernetics, 2018

2017

General relation-based variable precision rough fuzzy set.

Eric C. C. Tsang, Bingzhen Sun, Weimin Ma

Int. J. Mach. Learn. Cybern., 2017

Minimal decision cost reduct in fuzzy decision-theoretic rough set model.

Jingjing Song, Eric C. C. Tsang, Degang Chen, Xibei Yang

Knowl. Based Syst., 2017

Generalized dominance rough set models for the dominance intuitionistic fuzzy information systems.

Xiaoxia Zhang, Degang Chen, Eric C. C. Tsang

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

Double-quantitative rough fuzzy set based decisions: A logical operations method.

Bingjiao Fan, Eric C. C. Tsang, Weihua Xu, Jianhang Yu

Inf. Sci., 2017

Monotonic classification extreme learning machine.

Hong Zhu, Eric C. C. Tsang, Xi-Zhao Wang, Rana Aamir Raza Ashfaq

Neurocomputing, 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

Discrete differential evolutions for the discounted {0-1} knapsack problem.

Hong Zhu, Yi-Chao He, Xizhao Wang, Eric C. C. Tsang

Int. J. Bio Inspired Comput., 2017

Fuzzy rough set based incremental attribute reduction from dynamic data with sample arriving.

Yanyan Yang, Degang Chen, Hui Wang, Eric C. C. Tsang, Deli Zhang

Fuzzy Sets Syst., 2017

A new compound arithmetic crossover-based genetic algorithm for constrained optimisation in enterprise systems.

Chenxia Jin, Fachao Li, Eric C. C. Tsang, Larissa Bulysheva, Mikhail Yu. Kataev

Enterp. Inf. Syst., 2017

Weights based ranked fuzzy rough reduction.

Eric C. C. Tsang, Fan Xingqi, Xuefeng Li, Suyun Zhao

Proceedings of the 2017 International Conference on Machine Learning and Cybernetics, 2017

A weighted multi-granulation decision-theoretic approach to multi-source decision systems.

Yanting Guo, Eric C. C. Tsang, Weihua Xu

Proceedings of the 2017 International Conference on Machine Learning and Cybernetics, 2017

2016

Data-Distribution-Aware Fuzzy Rough Set Model and its Application to Robust Classification.

Shuang An, Qinghua Hu, Witold Pedrycz, Pengfei Zhu, Eric C. C. Tsang

IEEE Trans. Cybern., 2016

Feature and instance reduction for PNN classifiers based on fuzzy rough sets.

Eric C. C. Tsang, Qinghua Hu, Degang Chen

Int. J. Mach. Learn. Cybern., 2016

Multi-label learning with label-specific feature reduction.

Suping Xu, Xibei Yang, Hualong Yu, Dong-Jun Yu, Jingyu Yang, Eric C. C. Tsang

Knowl. Based Syst., 2016

Neighborhood collaborative classifiers.

Suping Xu, Xibei Yang, Eric C. C. Tsang, Eric Appiah Mantey

Proceedings of the International Conference on Machine Learning and Cybernetics, 2016

Random analysis of statistical rough set.

Eric C. C. Tsang, Su-Yun Zhao

Proceedings of the International Conference on Machine Learning and Cybernetics, 2016

Minimum decision cost reduct for fuzzy decision-theoretic rough set model.

Jingjing Song, Eric C. C. Tsang, Degang Chen, Xibei Yang

Proceedings of the International Conference on Machine Learning and Cybernetics, 2016

2015

The comparative study of fuzzy rough reduction.

Eric C. C. Tsang, Suyun Zhao

Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, 2015

Basic properties of fuzzy approximation operators under consistent functions.

Eric C. C. Tsang, Changzhong Wang, Yang Du, Qiang He

Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, 2015

A method to fuzzy multi-objective problems under random environment.

Eric C. C. Tsang, Jing-Duo Jie, Chen-Xia Jin

Proceedings of the 2015 International Conference on Machine Learning and Cybernetics, 2015

2014

A Fast Algorithm to Building a Fuzzy Rough Classifier.

Eric C. C. Tsang, Suyun Zhao

Proceedings of the Machine Learning and Cybernetics, 2014

Neighbourhood-assignment attribute reduction based on general binary relations.

Eric C. C. Tsang, Changzhong Wang, Du Yan, Jiaze Li

Proceedings of the 2014 International Conference on Machine Learning and Cybernetics, 2014

Face Recognition Using Genetic Algorithm.

Qin Qing, Eric C. C. Tsang

Proceedings of the Machine Learning and Cybernetics, 2014

2013

Communication Between Information Systems Using Fuzzy Rough Sets.

Eric C. C. Tsang, Changzhong Wang, Degang Chen, Congxin Wu, Qinghua Hu

IEEE Trans. Fuzzy Syst., 2013

Nested structure in parameterized rough reduction.

Suyun Zhao, Xizhao Wang, Degang Chen, Eric C. C. Tsang

Inf. Sci., 2013

The topological structure in parameterized rough sets.

Eric C. C. Tsang, Suyun Zhao

Proceedings of the International Conference on Machine Learning and Cybernetics, 2013

Generalized variable precision probabilistic rough set.

Eric C. C. Tsang, Bingzhen Sun

Proceedings of the International Conference on Machine Learning and Cybernetics, 2013

Attribute reduction and attribute characteristics of formal contexts.

Eric C. C. Tsang, Ming-Wen Shao

Proceedings of the International Conference on Machine Learning and Cybernetics, 2013

2012

Attribute reduction based on interval valued fuzzy granules.

Eric C. C. Tsang, S. Y. Zhao

Proceedings of the International Conference on Machine Learning and Cybernetics, 2012

Variable precision rough fuzzy set model based on general relations.

Eric C. C. Tsang, Weimin Ma, Bingzhen Sun

Proceedings of the International Conference on Machine Learning and Cybernetics, 2012

An attribute reduction method based on core samples set.

Eric C. C. Tsang, Chen-Xia Jin, Degang Chen, Fa-Chao Li

Proceedings of the International Conference on Machine Learning and Cybernetics, 2012

2011

A property of reductions in Fuzzy Variable Precision Rough Set model.

Eric C. C. Tsang, Suyun Zhao, Cai-Li Zhou

Proceedings of the International Conference on Machine Learning and Cybernetics, 2011

2010

Decision Table Reduction in KDD: Fuzzy Rough Based Approach.

Eric C. C. Tsang, Suyun Zhao

Trans. Rough Sets, 2010

Building a Rule-Based Classifier—A Fuzzy-Rough Set Approach.

Suyun Zhao, Eric C. C. Tsang, Degang Chen, Xizhao Wang

IEEE Trans. Knowl. Data Eng., 2010

On the fuzzy generalization of the Dempster-Shafer theory of evidence.

Eric C. C. Tsang, Degang Chen

Proceedings of the International Conference on Machine Learning and Cybernetics, 2010

Sample selection with rough set.

Degang Chen, Xiao Zhang, Eric C. C. Tsang, Yongping Yang

Proceedings of the International Conference on Machine Learning and Cybernetics, 2010

2009

The Model of Fuzzy Variable Precision Rough Sets.

Suyun Zhao, Eric C. C. Tsang, Degang Chen

IEEE Trans. Fuzzy Syst., 2009

2008

Hybridization of Fuzzy and Rough Sets: Present and Future.

Eric C. C. Tsang, Qingcai Chen, Suyun Zhao, Daniel S. Yeung, Xizhao Wang

Proceedings of the Fuzzy Sets and Their Extensions: Representation, Aggregation and Models, 2008

Nesting One-Against-One Algorithm Based on SVMs for Pattern Classification.

Bo Liu, Zhifeng Hao, Eric C. C. Tsang

IEEE Trans. Neural Networks, 2008

Attributes Reduction Using Fuzzy Rough Sets.

Eric C. C. Tsang, Degang Chen, Daniel S. Yeung, Xizhao Wang, John W. T. Lee

IEEE Trans. Fuzzy Syst., 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

On fuzzy approximation operators in attribute reduction with fuzzy rough sets.

Suyun Zhao, Eric C. C. Tsang

Inf. Sci., 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

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

Approximations and reducts with covering generalized rough sets.

Eric C. C. Tsang, Degang Chen, Daniel S. Yeung

Comput. Math. Appl., 2008

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

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 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

Ellipsoidal support vector clustering for functional MRI analysis.

Defeng Wang, Lin Shi, Daniel S. Yeung, Eric C. C. Tsang, Pheng-Ann Heng

Pattern Recognit., 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

Learning fuzzy rules from fuzzy samples based on rough set technique.

Xizhao Wang, Eric C. C. Tsang, Suyun Zhao, Degang Chen, Daniel S. Yeung

Inf. Sci., 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

Stability analysis of a discrete Hopfield neural network with delay.

Eric C. C. Tsang, S. S. Qiu, Daniel S. Yeung

Neurocomputing, 2007

Sample Reduction for SVMs via Data Structure Analysis.

Defeng Wang, Daniel S. Yeung, Eric C. C. Tsang

Proceedings of the 2nd IEEE International Conference on System of Systems Engineering, 2007

An approach of attributes reduction based on fuzzy TL rough sets.

Degang Chen, Eric C. C. Tsang, Suyun Zhao

Proceedings of the IEEE International Conference on Systems, 2007

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

Proceedings of the IEEE International Conference on Systems, 2007

2006

Structured One-Class Classification.

Defeng Wang, Daniel S. Yeung, Eric C. C. Tsang

IEEE Trans. Syst. Man Cybern. Part B, 2006

Preface for the special issue: soft computing in machine learning and cybernetics in the journal <i>Soft Computing</i>.

Zhi-Qiang Liu, Daniel S. Yeung, Xizhao Wang, Eric C. C. Tsang, John W. T. Lee

Soft Comput., 2006

Rough sets and ordinal reducts.

John W. T. Lee, Daniel S. Yeung, Eric C. C. Tsang

Soft Comput., 2006

Rough approximations on a complete completely distributive lattice with applications to generalized rough sets.

Degang Chen, Wenxiu Zhang, Daniel S. Yeung, Eric C. C. Tsang

Inf. Sci., 2006

A Discussion of Attribute Reduction in Fuzzy Rough Sets Using Support Vector Machine.

Eric C. C. Tsang, Degang Chen, Suyun Zhao, Qiang He

Proceedings of the IEEE International Conference on Systems, 2006

Structured Large Margin Machine Ensemble.

Patrick P. K. Chan, Defeng Wang, Eric C. C. Tsang, Daniel S. Yeung

Proceedings of the IEEE International Conference on Systems, 2006

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

Proceedings of the IEEE International Conference on Systems, 2006

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

On the generalization of fuzzy rough sets.

Daniel S. Yeung, Degang Chen, Eric C. C. Tsang, John W. T. Lee, Xizhao Wang

IEEE Trans. Fuzzy Syst., 2005

Hierarchical clustering based on ordinal consistency.

John W. T. Lee, Daniel S. Yeung, Eric C. C. Tsang

Pattern Recognit., 2005

An Approach To Case-Based Maintenance: Selecting Representative Cases.

Eric C. C. Tsang, Xizhao Wang

Int. J. Pattern Recognit. Artif. Intell., 2005

Some notes on equivalent fuzzy sets and fuzzy subgroups.

Degang Chen, Jiashang Jiang, Congxin Wu, Eric C. C. Tsang

Fuzzy Sets Syst., 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

Proceedings of the IEEE International Conference on Systems, 2005

On attributes reduction with fuzzy rough sets.

Gloria C. Y. Tsang, Degang Chen, Eric C. C. Tsang, John W. T. Lee, Daniel S. Yeung

Proceedings of the IEEE International Conference on Systems, 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

Proceedings of the IEEE International Conference on Systems, 2005

A feature space analysis for anomaly detection.

Shuyuan Jin, Daniel S. Yeung, Xizhao Wang, Eric C. C. Tsang

Proceedings of the IEEE International Conference on Systems, 2005

Support Vector Clustering for Brain Activation Detection.

Defeng Wang, Lin Shi, Daniel S. Yeung, Pheng-Ann Heng, Tien-Tsin Wong, Eric C. C. Tsang

Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 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

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 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

Proceedings of the Advances in Machine Learning and Cybernetics, 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

Proceedings of the Advances in Machine Learning and Cybernetics, 2005

A Covariance Matrix Based Approach to Internet Anomaly Detection.

Shuyuan Jin, Daniel S. Yeung, Xizhao Wang, Eric C. C. Tsang

Proceedings of the Advances in Machine Learning and Cybernetics, 2005

Refinement of Fuzzy Production Rules by Using a Fuzzy-Neural Approach.

Dongmei Huang, Minghu Ha, Ya-min Li, Eric C. C. Tsang

Proceedings of the Advances in Machine Learning and Cybernetics, 2005

On the Local Reduction of Information System.

Degang Chen, Eric C. C. Tsang

Proceedings of the Advances in Machine Learning and Cybernetics, 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

Proceedings of the Advances in Machine Learning and Cybernetics, 2005

Gene Selection Through Sensitivity Analysis of Support Vector Machines.

Defeng Wang, Daniel S. Yeung, Eric C. C. Tsang, Lin Shi

Proceedings of the Computational Life Sciences, First International Symposium, 2005

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

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

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

2003

OFFSS: optimal fuzzy-valued feature subset selection.

Eric C. C. Tsang, Daniel S. Yeung, Xizhao Wang

IEEE Trans. Fuzzy Syst., 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

Int. J. Pattern Recognit. Artif. Intell., 2003

Selecting representative cases by generalization capability.

Eric C. C. Tsang, Xi-Zhao Wang

Proceedings of the IEEE International Conference on Systems, 2003

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

Ordinal fuzzy sets.

John Wan Tung Lee, Daniel S. Yeung, Eric C. C. Tsang

IEEE Trans. Fuzzy Syst., 2002

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

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

Learning weights of fuzzy production rules by a max-min neural network.

Eric C. C. Tsang, Daniel S. Yeung, Xi-Zhao Wang

Proceedings of the IEEE International Conference on Systems, 2001

A General Updating Rule for Discrete Hopfield-Type Neural Network with Delay.

Shenshan Qiu, Eric C. C. Tsang, Daniel S. Yeung, Xizhao Wang

Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

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

Refinement of fuzzy production rules by neuro-fuzzy networks.

Eric C. C. Tsang, Shenshan Qiu, Daniel S. Yeung

Proceedings of the IEEE International Conference on Systems, 2000

Fuzzy weighted classification rules induction from data.

Eric C. C. Tsang, Hongbing Li, Daniel S. Yeung, John W. T. Lee

Proceedings of the IEEE International Conference on Systems, 2000

Mining fuzzy association rules with weighted items.

Yue Joyce Shu, Eric C. C. Tsang, Daniel S. Yeung, Daming Shi

Proceedings of the IEEE International Conference on Systems, 2000

Stability of discrete Hopfield neural networks with time-delay.

Shenshan Qiu, Eric C. C. Tsang, Daniel S. Yeung

Proceedings of the IEEE International Conference on Systems, 2000

1999

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

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

Refinement of knowledge representation parameters in fuzzy production rules by genetic algorithms.

Eric C. C. Tsang, Daniel S. Yeung, John W. T. Lee

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1998

Refining local weights and certainty factors using a fuzzy neural network.

Eric C. C. Tsang, Daniel S. Yeung

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1998

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

Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1998

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

Weighted fuzzy production rules.

Daniel S. Yeung, Eric C. C. Tsang

Fuzzy Sets Syst., 1997

Acquiring and tuning knowledge representation parameters of fuzzy production rules using fuzzy expert networks.

Eric C. C. Tsang, Daniel S. Yeung

Proceedings of the Knowledge-Based Intelligent Electronic Systems, 1997

1994

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