Cheung, Yiu-ming

Dr. Yiu-ming CHEUNG (張曉明博士)

M.Phil., Ph.D. , Senior Member, ACM, Senior Member, IEEE

Associate Professor

Department of Computer Science

Hong Kong Baptist University

Mail Address:

7/F, Department of Computer Science,
Sir Run Run Shaw Building,
Hong Kong Baptist University,
Kowloon Tong, Kowloon, Hong Kong.

郵寄地址:
香港九龍塘浸會大學邵逸夫大樓七樓計算機科學系

Tel: (+852) 3411 5155

Fax: (+852) 3411 7892

E-mail: ymc@comp.hkbu.edu.hk

You are the -th visitor to this page since January 18, 2004.

About me

Profile

Yiu-ming Cheung received Ph.D. degree from Department of Computer Science and Engineering at The Chinese University of Hong Kong in 2000. He joined the Department of Computer Science at Hong Kong Baptist University in 2001, and then became an Associate Professor in 2005. He is the senior member of IEEE and ACM.

His current research interests are in the fields of Machine Learning and Information Security, particularly the topics on Clustering Analysis, Blind Source Separation, Neural Networks, Nonlinear Optimization, Watermarking and Lip-reading. He is the (founding) Chairman of IEEE (Hong Kong) Computational Intelligence Chapter. He has taken the key positions (e.g., Organizing Committee Chair, Programme Committee Chair, Financial Chair etc.) in several major international conferences, including The 2006 IEEE International Conference on Data Mining (ICDM'2006) and The 2006 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology (WI-IAT'2006). Currently, he is the Associate Editor of Knowledge and Information Systems (KAIS), as well as the Guest Co-editor and Editorial Board member of the several international journals.

International Software Competition

Yiu-ming Cheung and his partner proposed a novel approach and developed a software accordingly to participate in the worldwide International Nonlinear Financial Forecasting Competition (INFFC), held in USA in 1995. In this competition, all participated software were tested using real-life financial data, and evaluated by more than 12 major performance evaluation indices. The perforamnce of their developed software is at either first-place or second place under the measurement of these major indices. The detailed competition results, including the performance assessment of their software by a set of indices, are both published in the Proceedings of the First INFFC, edited by Randall B. Caldwell, Finance & Technology Publishing, 1997.

Selected Publications

Selected Refereed Journals (Sorted by Reverse Chronological Order)

Y.M. Cheung and H. Zeng, "Local Kernel Regression Score for Selecting Features of High-dimensional Data", IEEE Transactions on Knowledge and Data Engineering, in press.

H.T. Wu and Y.M. Cheung, "Reversible Watermarking by Modulation and Security Enhancement", IEEE Transactions on Instrumentation and Measurement, in press.

H. Zeng and Y.M. Cheung, "A New Feature Selection Method for Gaussian Mixture Clustering", Pattern Recognition, Vol. 42, No. 2, pp. 243-250, 2009.

Mark J. Li, Michael K. Ng, Y.M. Cheung and Joshua Z.X. Huang, "Agglomerative Fuzzy K-Means Clustering Algorithm with Selection of Number of Clusters", IEEE Transactions on Knowledge and Data Engineering, Vol. 20, No. 11, pp. 1519-1534, 2008.

Y.M. Cheung and H.T. Wu, "A Sequential Quantization Strategy for Data Embedding and Integrity Verification", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 17, No. 8, pp. 1007-1016, 2007.

Z.Y. Zhang and Y.M. Cheung, "On Weight Design of Maximum Weighted Likelihood and an Extended EM Algorithm", IEEE Transactions on Knowledge and Data Engineering, Vol. 18, No. 10, pp. 1429-1434, 2006.

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, Vol. 17, No. 6, pp. 750--761, 2005. [ Supplementary Materials (pdf), Source Code (zip)]

Y.M. Cheung, "On Rival Penalization Controlled Competitive Learning for Clustering with Automatic Cluster Number Selection", IEEE Transactions on Knowledge and Data Engineering, Vol. 17, No. 11, pp. 1583-1588, 2005.

Y.M. Cheung and R.B. Huang, "A Divide-and-Conquer Learning Approach to Radial Basis Function Networks", Neural Processing Letters, Vol. 21, No. 3, pp. 189-206, 2005.

X.M. Zhao, Y.M. Cheung and D.S. Huang, "A Novel Approach to Extracting Features from Motif Content and Protein Composition for Protein Sequence Classification", Neural Networks, Vol. 18, No. 8, pp. 1019-1028, October, 2005.

Y.M. Cheung , "k*-Means: A New Generalized k-Means Clustering Algorithm", Pattern Recognition Letters, Vol. 24, Issue 15, pp. 2883--2893, 2003.

Y.M. Cheung and L. Xu, "Dual Multivariate Auto-regressive Modeling in State Space for Temporal Signal Separation", IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics, Vol. 33, No. 3, pp. 386-398, June, 2003.

K.K. Hung, Y.M. Cheung and L. Xu, "An Extended ASLD Trading System to Enhance Portfolio Management", IEEE Transactions on Neural Networks, Vol. 14, No. 2, pp. 413--425, March, 2003.

Y.M. Cheung and L. Xu, "Further Studies on Temporal Factor Analysis: Comparison and Kalman Filter Based Algorithm", Neurocomputing, Vol. 50, pp. 87-103, January, 2003.

Y.M. Cheung and L. Xu, "Independent Component Ordering in ICA Time Series Analysis", Neurocomputing, Vol. 41, pp. 145-152, 2001.

Y.M. Cheung and L. Xu, "An RPCL-based Approach for Identification of Markov Model with Unknown State Number", IEEE Signal Processing Letters, Vol. 7, No. 10, pp. 284-287, October, 2000.

Selected Refereed Conference Papers (Sorted by Reverse Chronological Order)

M. Li and Y.M. Cheung, "A Novel Motion Based Lip Feature Extraction for Lip-reading", Proceedings of 2008 International Conference on Computational Intelligence and Security (CIS'08), pp. 361-365, 2008.

T. Li, W.J. Pei, S.P. Wang and Y.M. Cheung, "Cooperation Controlled Competitive Learning Approach for Data Clustering", Proceedings of 2008 International Conference on Computational Intelligence and Security (CIS'08), pp. 24-29, 2008.

H.T. Wu, J.L. Dugelay and Y.M. Cheung, "A Data Mapping Method for Steganography and Its Application to Images", Proceedings of Information Hiding (IH'2008), LNCS 5284, pp. 236-250, 2008.

H. Zeng and Y.M. Cheung, "Feature Selection for Clustering on High Dimensional Data", Proceedings of Tenth Pacific Rim International Conference on Artificial Intelligence (PRICAI'08), LNAI 5351, pp. 913-922, 2008.

P. Winoto and Y.M. Cheung and J.M. Liu, "Mechanism Design for Clustering Aggregration by Selfish Systems", Proceedings of 7th IEEE International Conference on Data Mining (ICDM'07), pp. 703-708, 2007.

Y.M. Cheung and H. Zeng, "A Maximum Weighted Likelihood Approach to Model Selection and Feature Weighting in Gaussian Mixture", Proceedings of 2007 International Conference on Artificial Neural Networks (ICANN'07), LNCS 4668, Part I: pp. 78-87, 2007.

H. Zeng and Y.M. Cheung, "Iterative Feature Selection in Gaussian Mixture Clustering with Automatic Model Selection", Proceedings of the 2007 International Joint Conference on Neural Networks (IJCNN'07), pp. 2277-2282, 2007.

Y.M. Cheung and H. Zeng, "Feature Weighted Rival Penalized EM for Gaussian Mixture Clustering: Automatic Feature and Model Selections in a Single Paradigm", Post-conference Proceedings of the 2006 International Conference on Computational Intelligence and Security, Lecture Notes in Artificial Intelligence (LNAI 4456), pp. 1018-1028, 2007.

H.T. Wu and Y.M. Cheung, "A High-Capacity Data Hiding Method for Polygonal Meshes", Proceedings of 8th Information Hiding (IH'06), 2006.

H.T. Wu and Y.M. Cheung, "A New Fragile Mesh Watermarking Algorithm for Authentication", Proceedings of The 20th IFIP International Information Security Conference (SEC 2005), pp. 509--523, Japan, May 30-June 1, 2005.

H.T. Wu and Y.M. Cheung, "A Fragile Watermarking Approach to 3D Meshes Authentication", Proceedings of the 7th Workshop on Multimedia & Security (ACM'05), pp. 117-123, 2005.

H.L. Liu and Y.M. Cheung, "A Learning Framework for Blind Source Separation Using Generalized Eigenvalues", Proceedings of International Symposium on Neural Network, LNCS 3497, pp. 472--477, Chongqin, 2005.

Y.M. Cheung, "A Rival Penalized EM Algorithm towards Maximizing Weighted Likelihood for Density Mixture Clustering with Automatic Model Selection", Proceedings of the 17th International Conference on Pattern Recognition (ICPR'04), Vol. 4, pp. 633-636, Cambridge, United Kingdom, 2004.

Y.M. Cheung, "A Competitive and Cooperative Learning Approach to Robust Data Clustering", Proceedings of the IASTED International Conference of Neural Networks and Computational Intelligence (NCI'2004), pp. 131-136, Grindelwald, Switzerland, 2004.

Y.M. Cheung and Hailin Liu, "A New Approach to Blind Source Separation with Global Optimal Property", Proceedings of the IASTED International Conference of Neural Networks and Computational Intelligence (NCI'2004), pp. 137-141, Grindelwald, Switzerland, 2004.

Y.M. Cheung, "Expectation-MiniMax Approach to Clustering Analysis", Proceedings of Joint 13th International Conference on Artificial Neural Networks and 10th International Conference on Neural Information Processing (ICANN/ICONIP 2003), pp. 165--172, Lecture Notes in Computer Science 2714, Springer Publisher, Turkey, June 26-29, 2003.

Y.M. Cheung and R.B. Huang, "An Advance on Divide-and-Conquer Based Radial Basis Function Networks", Proceedings of Fourth International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'2003), pp. 143--150, Springer Publisher, Hong Kong, March 21-23, 2003.

L.T. Law and Y.M. Cheung, "Color Image Segmentation Using Rival Penalized Controlled Competitive Learning", Proceedings of 2003 International Joint Conference on Neural Networks (IJCNN'2003), Portland, Oregon, USA, July 20-24, 2003.

Y.M. Cheung, "Rival Penalization Controlled Competitive Learning for Data Clustering with Unknown Cluster Number", Proceedings of 9th International Conference on Neural Information Processing (Paper ID: 1983 in CD-ROM Proceeding) , Singapore, November 18-22, 2002.

Y.M. Cheung, "A New Recurrent Radial Basis Function Network", Proceedings of 9th International Conference on Neural Information Processing (Paper ID: 1538 in CD-ROM Proceeding) , Singapore, November 18-22, 2002.

Y.M. Cheung, "Temporal Principal Component Analysis --- Advances in Dual Auto-regressive Modeling for Blind Gaussian Process Identification", Proceedings of 2002 IEEE International Conference on Systems, Man and Cybernetics(SMC'2002), (Paper Code: TA1F4 in CD-ROM Proceedings). Hammamet, Tunisia, October 6-9, 2002.

R.B. Huang, L.T. Law and Y.M. Cheung, "An Experimental Study: On Reducing RBF Input Dimension By ICA and PCA", Proceedings of 1st IEEE International Conference on Machine Learning and Cybernetics (ICMLC'2002), Vol. 4, pp. 1941-1946, November 4-5, Beijing, 2002.

R.B. Huang, Y.M. Cheung and L.T. Law, "A Divide-and-Conquer Fast Implementation of Radial Basis Function Network with Application to Time Series Forecasting", Workshop of Advances in Data Mining and Modelling, pp. 97-106, Hong Kong, June 27-28, 2002.

Y.M. Cheung, "Dual Auto-Regressive Modelling Approach to Gaussian Process Identification", Proceedings of 2001 IEEE International Conference on Multimedia and Expo (ICME2001), pp. 1256-1259, Tokyo, Japan, 2001.

Book Chapter

Z.B. Lai, Y.M. Cheung and L. Xu, "Independent Component Ordering in ICA Analysis of Financial Data", Computational Finance, Chapter 14, pp. 201-212, edited by Yaser S. Abu-Mostafa, Blake LeBaron, Andrew W. Lo and Andreas S. Weigend, The MIT Press, 1999.

Co-Edited Books

(1) Computational Intelligence and Security, Lecture Notes in Artificial Intelligence (LNAI) (Part I: LNAI 3801, Part II: LNAI 3802), Springer, 2005.

(2) Intelligent Data Engineering and Automated Learning, Lecture Notes in Computer Science (LNCS 2690), Springer, 2003.