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香港浸会大学HongKongBaptistUniversity计算机科学系老师简介-Prof. CHEUNG, Yiu Ming

本站小编 Free考研考试/2022-02-04

Prof. CHEUNG, Yiu Ming

張曉明教授
B.Sc., M.Phil., Ph.D., FIEEE, FAAAS, FIET, FBCS
Professor, Department of Computer Science

https://www.comp.hkbu.edu.hk/~ymc



AboutProf. Cheung received the PhD degree from the Department of Computer Science and Engineering at the Chinese University of Hong Kong. Currently, he is a Full Professor at the Computer Science Department in Hong Kong Baptist University (HKBU). Also, he is serving as an Associate Editor in IEEE Transactions on Cybernetics, IEEE Transactions on Emerging Topics in Computational Intelligence,IEEE Transactions on Cognitive and Developmental Systems, Pattern Recognition, andNeurocomputing, to name a few. Prof. Cheung iselected as aDistinguished Lecturer of IEEE Computational Intelligence Society in 2020, andthe Changjiang Chair Professor awarded by Ministry of Education of China.

Research InterestsMachine Learning
Data Science
Visual Computing
Pattern Recognition
Multi-objective Optimization
Information Hiding

Selected PublicationsY.Q. Zhang and Y.M. Cheung*, “Learnable Weighting of Intra-attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes”, IEEE Transactions on Pattern Analysis and Machine Intelligence, DOI:10.1109/TPAMI.2021.3056510.
X. Liu, K. Hu, H.B. Ling andY.M. Cheung*, “MTFH: A Matrix Tri-Factorization Hashing Framework for Efficient Cross-Modal Retrieval”,IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(3): 964-981, 2021.
Y. Zhou andY.M. Cheung*, “Bayesian Low-Tubal-Rank Robust Tensor Factorization with Multi-Rank Determination”,IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(1): 62-76, 2021.
J. Lou andY.M. Cheung*, “Robust Low-rank Tensor Minimization via a New Tensor Spectralk-Support Norm”,IEEE Transactions on Image Processing, 29(1): 2314-2327, 2020.
Y. Lu,Y.M. Cheung*and Y.Y. Tang, “Bayes Imbalance Impact Index: A Measure of Class Imbalanced Dataset for Classification Problem”,IEEE Transactions on Neural Networks and Learning Systems, 31(9): 3525-3539, 2020.
Y.M. Cheung*, F.Q. Gu, H.L. Liu, K.C. Tan and H. Huang, “Objective-Domain Dual Decomposition: An Effective Approach to Optimizing Partial Differentiable Objective Functions”,IEEE Transactions on Cybernetics, 50(3): 923-934, 2020.
Y.M. Cheung*and Y.Q. Zhang, “Fast and Accurate Hierarchical Clustering Based on Growing Multi-Layer Topology Training”,IEEE Transactions on Neural Networks and Learning Systems, 30(3): 876-890, 2019.
X. Liu andY.M. Cheung*, "Learning Multi-Boosted HMMs for Lip-Password Based Speaker Verification",IEEE Transactions on Information Forensics and Security, 9(2): 233-246, 2014.
H. Zeng and Y.M. Cheung*, “Feature Selection and Kernel Learning for Local Learning Based Clustering”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(8): 1532-1547, 2011.
Y.M. Cheung, “Maximum Weighted Likelihood via Rival Penalized EM for Density Mixture Clustering with Automatic Model Selection”, IEEE Transactions on Knowledge and Data Engineering, 17(6): 750-761, 2005.
(Note: * Corresponding Author)


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