
CHEUNG, Yiuming (張曉明), PhD, IEEE Fellow,
IET Fellow,

Profile:
Yiuming
Cheung is a
Full Professor of Department
of Computer Science and
an
Associate Director of Institute
of Computational and Theoretical Studies at Hong Kong Baptist University (HKBU). He
received PhD degree from Department of Computer Science and Engineering at The
Chinese University of Hong Kong in 2000, and then joined the Department of
Computer Science at HKBU in 2001. He is
an IEEE Fellow, IET/IEE Fellow, British Computer Society (BCS) Fellow, Fellow
of the Royal Society of Arts (RSA), and Distinguished Fellow of International
Engineering and Technology Institute, Hong Kong (IETI), as well as the “Chu
Tian Scholars (楚天學者)” in China.
His
research interests include Artificial
Intelligence, Intelligent Visual Computing,
Pattern Recognition, Data
Mining, Watermarking,
and Optimization. He has published over 220
articles in the highquality conferences and journals, including IEEE
Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on
Neural Networks and Learning Systems, IEEE Transactions on Information
Forensics and Security, IEEE Transactions on Image Processing, IEEE
Transactions on Knowledge and Data Engineering, IEEE Transactions on SMC (Part B),
Pattern Recognition, and so on. His coauthored work on multimodal optimization
won the championship in the competition of MultiNiche Optimization held in
CEC’2015  a flagship international conference on Evolutionary Computation.
Moreover, he has been granted one Chinese patent and two US patents. In
particular, selected from 1000 new inventions and products of 700+ competition
teams from 40 countries, he was awarded two most prestigious prizes: (1) the
Gold Medal with Distinction (i.e. the highest grade in Gold Medals) and (2)
Swiss Automobile Club Prize, in the 45^{th} International Exhibition of
Invention, Geneva, Switzerland, on March 29April 2, 2017, in recognition of
his innovative work. Also, he was the Gold Award Winner of Hong Kong Innovative
Invention Award in the Seventh Hong Kong Innovative Technologies Achievement
Award 2017. In addition, he won the Gold Medal with Congratulations of Jury
(i.e. the highest grade in Gold Medals) and the Award of Excellence from
Romania, respectively, at the 46th International Exhibition of Inventions of
Geneva 2018 with his invention “Lippassword: Double Security System for
Identity Authentication”. Prof. Cheung was the
recipient of 2011 Best Research Award in Department of Computer Science, HKBU, the recipient of Best
Paper Awards in SEAL’2017, ISICA’2017, ICNCFSKD’2014, and IEEE
IWDVT’2005, respectively, and the recipient
of 2017 IETI Annual Scientific Award. He has been recognized as the recipient
of 2017 & 2018 Albert Nelson Marquis Lifetime Achievement Award.
He
is the Founding
Chairman of IEEE (Hong Kong) Computational Intelligence Chapter and the Chair of Technical
Committee on Intelligent Informatics (TCII) of IEEE Computer Society. He
has served in various capacities (e.g.,
Organizing Committee Chair, Program Committee Chair, Program Committee Area Chair, Financial
Chair,
Senior Program Committee Member, etc.) at
several toptier
international
conferences, including IEEEsponsored
IJCAIECAI’2018, ICDM’2017 & 2018, WCCI’2016, WIIAT’2012,
ICDM’2006
& WIIAT’2006.
Currently, he is the Associate Editor of several prestigious journals,
including IEEE Transactions on Neural Networks and Learning Systems, IEEE
Transactions on Cybernetics, Pattern Recognition, Knowledge
and Information Systems (KAIS), International Journal of Pattern Recognition and
Artificial Intelligence, and Neurocomputing, as
well as the Guest Coeditor
in
several international journals.
International
Software Competition:
Yiuming
Cheung,
as the lead author, has
proposed
a novel approach and developed software accordingly to participate in the
worldwide International Nonlinear Financial Forecasting Competition (INFFC),
held in USA in 1995. In this competition, all participated software was
tested using reallife financial data, and evaluated by more than 12 major
performance evaluation indices. The performance of their developed software is
at either firstplace 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.
The List of Patents:
1. “Method and Apparatus for Eye
Gaze Tracking ” [US Patent: US9,563,805];
2.
“A Lippassword Based Speaker Verification System” [US Patent: US9,159,321B2, Video: Mandarin, English];
3. "An
InfraredSpectrum Based Recognition System for Identifying Chinese Herbal
Species, Origins and Growth Mode with Highrecognition Rate" [Chinese Patent:
ZL200810005068.3, Introduction].
I. Selected Refereed
Journals (Sorted by Reverse Chronological Order)
[J.059] Q.M.
Peng and Y.M. Cheung, “Automatic
Video Object Segmentation Based on Visual and Motion Saliency”, IEEE Transactions on Multimedia, DOI:10.1109/TMM.2019.2918730.
[J.058] Y.
Lu, Y.M. Cheung and Y.Y. Tang,
“SelfAdaptive MultiPrototypebased Competitive Learning Approach: A
kmeanstype Algorithm for Imbalanced Data Clustering”, IEEE Transactions on Cybernetics, DOI:10.1109/TCYB.2019.2916196.
[J.057] Y.
Zhou, H.P. Lu and Y.M. Cheung,
“Probabilistic RankOne Tensor Analysis with Concurrent Regularizations”, IEEE Transactions on Cybernetic, DOI:
10.1109/TCYB.2019.2914316 [Source Code].
[J.056] Y.Q.
Zhang, Y.M. Cheung and K.C. Tan, “A
Unified EntropyBased Distance Metric for OrdinalandNominalAttribute Data
Clustering”, IEEE Transactions on Neural
Networks and Learning Systems, DOI: 10.1109/TNNLS.2019.2899381.
[J.055] M.
Pang, Y.M. Cheung, B.H. Wang and
R.S. Liu, “Robust Heterogeneous
Discriminative Analysis for Face Recognition with Single Sample per Person”,
Pattern Recognition, Vol. 89, pp.
91107, 2019 [DOI: 10.1016/j.patcog.2019.01.005, Source Code].
[J.054] X.
Liu, J.J. Geng, H.B. Ling and Y.M. Cheung, “Attention Guided
Deep Audioface Fusion for Efficient Speaker Naming”, Pattern Recognition, Vol. 88, pp. 557568, 2018.
[J053] M. Pang, Y.M. Cheung, R.S. Liu, J. Lou and C.
Lin, “Toward Efficient Image Representation: Sparse Concept Discriminant Matrix
Factorization”, IEEE Transactions on
Circuits and Systems for Video Technology, [DOI:
10.1109/TCSVT.2018.2879833, Source Code].
[J.052] S.Y.
Yi, Z.Y. He, Y. Li and Y.M. Cheung,
“Dual Pursuit for Subspace
Learning”, IEEE Transactions on
Multimedia, Vol. 21, No. 6, pp. 13991411, June 2019 [DOI:10.1109/TMM.2018.2877888].
[J.051] Q.Q.
Shi, Y.M. Cheung, Q.B. Zhao and H.P.
Lu, “Feature Extraction
for Incomplete Data via Lowrank Tensor Decomposition with Feature
Regularization”, IEEE Transactions on
Neural Networks and Learning Systems, Vol. 30, No. 6, pp. 18031817, June
2019 [DOI:10.1109/TNNLS.2018.2873655].
[J.050] Y.M. Cheung, F.Q. Gu, H.L. Liu, K.C. Tan and H. Huang, “ObjectiveDomain
Dual Decomposition: An Effective Approach to Optimizing Partial Differentiable
Objective Functions”,
IEEE Transactions on Cybernetics,
DOI: 10.1109/TCYB.2018.2870487.
[J.049]
Y. Zhou and Y.M. Cheung,
“Probabilistic RankOne Discriminant Analysis via Collective and Individual
Variation Modeling, IEEE Transactions on
Cybernetics, DOI:10.1109/TCYB.2018.2870440.
[J.048] X.
Liu and Y.M. Cheung, “On Incremental
Collaborative Appearance Model and Regional Particle Filtering for Lip Region
Tracking”, Integrated ComputerAided
Engineering, Vol. 25, pp. 6380, 2018 [DOI:10.3233/ICA170557].
[J.047] L.
Chen, H.L. Liu, K.C. Tan, Y.M. Cheung
and Y.P. Wang, “Evolutionary ManyObjective Algorithm Using Decomposition Based
Dominance Relationship”, IEEE
Transactions on Cybernetics [DOI: 10.1109/TCYB.2018.2859171].
[J.046] Y.M. Cheung and Y.Q. Zhang, “Fast
and Accurate Hierarchical Clustering Based on Growing MultiLayer Topology
Training”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 30, No. 3, pp. 876890, March 2019 [DOI: 10.1109/TNNLS.2018.2853407, Source Code].
[J.045] Q.Q.
Shi, H.P. Lu and Y.M. Cheung, “RankOne Matrix
Completion with Automatic Rank Estimation via L1Norm Regularization”, IEEE Transactions on Neural Networks
and Learning Systems, 29(10):47444757, October 2018 [DOI:
10.1109/TNNLS.2017.2766160, Source Code].
[J.044] J.B. Zeng, Y. Liu, B. Leng, Z. Xiong and Y.M.
Cheung, “Dimensionality
Reduction in Multiple Ordinal Regression”, IEEE Transactions on Neural Networks and Learning Systems,
29(9):40884101, September 2018 [DOI: 10.1109/TNNLS.2017.2752003].
[J.043] H. Jia and Y.M. Cheung,
“Subspace
Clustering of Categorical and Numerical Data With an Unknown Number of Clusters”,
IEEE Transactions on Neural Networks and
Learning Systems, 29(8):33083325, August 2018 [DOI:
10.1109/TNNLS.2017.2728138].
[J.042] F.Q.
Gu and Y.M.
Cheung, “Selforganizing
Mapbased Weight Design for Decompositionbased Manyobjective Evolutionary
Algorithm”, IEEE Transactions on
Evolutionary Computation, 22(2):211225, March 2018 [DOI:
10.1109/TEVC.2017.2695579].
[J.041] Y. Wang, J.W. Wan, J. Guo, Y.M. Cheung and P.C. Yuen, “Inferencebased
Similarity Search in Randomized Montgomery Domains for PrivacyPreserving
Biometric Identification”, IEEE
Transactions on Pattern Analysis and Machine Intelligence, 40(7):16111624,
July 2018 [DOI: 10.1109/TPAMI.2017.2727048].
[J.040] Y. Zhang, Y.M. Cheung and W.F. Su, “A Totalvariation
Constrained Permutation Model for Revealing Common Copy Number Patterns”, Scientific Reports, 7, Article Number:
9666, Nature, 2017 [DOI: 10.1038/s41598017091398].
[J.039] S.Y. Yi, Z.Y. He, Y.M. Cheung
and W.S. Chen, “Unified Sparse
Subspace Learning via Selfcontained Regression”, IEEE Transactions on Circuits and Systems for Video Technology,
28(10):25372550, October 2018 [DOI: 10.1109/TCSVT.2017.2721541].
[J.038] Y. Zhang, Y.M. Cheung, B. Xu and W.F. Su, “Detection Copy
Number Variants from NGS with Sparse and Smooth Constraints”, IEEE/ACM Transactions on Computational
Biology and Bioinformatics, 14(4):856867, August 2017 [DOI:
10.1109/TCBB.2016.2561933].
[J.037] X. Liu, H. Zhang, Y.M. Cheung,
X.G. You and Y.Y. Tang, “Efficient Single Image Dehazing and
Denosing: An Efficient Multiscale Correlated Wavelet Approach”, Computer Vision and Image Understanding,
Vol. 162, pp. 2333, 2017 [DOI: 10.1016/j.cviu.2017.08.002] [Source Code].
[J.036] X. Liu, G.F. He, S.J. Peng, Y.M. Cheung
and Y.Y. Tang, “Efficient
Human Motion Retrieval via Temporal Adjacent Bag of Words and Discriminative
Neighborhood Preserving Dictionary Learning”, IEEE Transactions on HumanMachine System, 47(6):763776, 2017 [DOI: 10.1109/THMS.2017.2675959].
[J.035] Y.M.
Cheung and J. Lou, “Proximal Average
Approximated Incremental Gradient Descent for Composite Penalty Regularized
Empirical Risk Minimization”, Machine
Learning, 106(4):595622, April 2017 [DOI: 10.1007/s1099401656091].
[J.034] Y.M. Cheung, M. Li, Q.M. Peng and
C.L. Philip Chen, “A Cooperative
Learningbased Clustering Approach to Lip Segmentation without Knowing Segment
Number”, IEEE Transactions on
Neural Networks and Learning Systems, 28(1):8093,
January 2017 [DOI:
10.1109/TNNLS.2015.2501547].
[J.033] Z.Y.
He, S.Y. Yi, Y.M. Cheung, X.G. You
and Y.Y. Tang, “Robust Object
Tracking via Key Patch Sparse Representation”, IEEE Transactions on Cybernetics, 47(2):354364, February 2017
[DOI: 10.1109/TCYB.2016.2514714].
[J.032] S.Y.
Yi, Z.H. Lai, Z.Y. He, Y.M. Cheung
and Y. Liu, “Joint
Sparse Principal Component Analysis”, Pattern
Recognition, Vol. 61, pp. 524536, 2017.
[J.031] Q.M. Peng, Y.M. Cheung, X.G. You and Y.Y. Tang, “A Hybrid of Local
and Global Saliencies for Detecting Image Salient Region and Appearance”, IEEE Transactions on Systems, Man and
Cybernetics: Systems, 47(1):8697, January 2017 [DOI: 10.1109/TSMC.2016.2564922].
[J.030] Y.M. Cheung, F.Q. Gu and H.L. Liu, “Objective Extraction
for ManyObjective Optimization Problems: Algorithm and Test Problems”, IEEE Transactions on Evolutionary
Computation, 20(5): 755772, October 2016.
[J.029] H. Jia, Y.M. Cheung
and J.M. Liu, “A
New Distance Metric for Unsupervised Learning of Categorical Data”, IEEE Transactions on Neural Networks and
Learning Systems,
Vol. 27, No. 5, pp. 10651079, 2016.
[J.028] X.
Liu, Y.M. Cheung and Y.Y. Tang, “Lip Event Detection
Using Oriented Histograms of Regional Optical Flow and Low Rank Affinity
Pursuit”, Computer Vision and Image
Understanding, Vol. 148, pp. 153163, 2016 [DOI: 10.1016/j.cviu.2015.11.015].
[J.027] P.Y.
Zhang, X.G. You, W.H. Ou, C.L. Philip Chen and Y.M. Cheung, “Sparse Discriminative
Multimanifold Embedding for Onesample Face Identification”, Patter Recognition, Vol. 52, pp.
249259, April 2016.
[J.026] Z.Q. Zhao, Y.M.
Cheung, H.B. Hu, and X.D. Wu, “Corrupted and
Occluded Face Recognition via Cooperative Sparse Representation”, Pattern Recognition, Vol. 56, pp. 7787,
August 2016.
[J.025] Y.
Wang, L.P. Wang, Y.M. Cheung and
P.C. Yuen, “Learning
Compact Binary
Codes for Hashbased Fingerprint Indexing”, IEEE Transactions on Information Forensics and Security, 10(8), pp.
16031616, 2015.
[J.024] Y.M.
Cheung
and Q.M. Peng, “Eye
Gaze Tracking with a Web Camera in a Desktop Environment”, IEEE Transactions on HumanMachine Systems,
45(4): 419430, 2015.
[J.023] Y.M.
Cheung,
M. Li, X. Cao and X.G. You,
"Lip Segmentation under
MAPMRF Framework with Automatic Selection
of Local Observation Scale and Number of Segments", IEEE
Transactions on Image Processing, Vol. 23,
No. 8, pp. 33973411, 2014.
[J.022] X. Liu and Y.M.
Cheung, "Learning
MultiBoosted HMMs for LipPassword Based Speaker Verification",
IEEE Transactions on Information Forensics and
Security, Vol. 9, No. 2, pp. 233246, 2014.
[J.021] H.Jia, Y.M. Cheung and
J. Liu, "Cooperative and Penalized Competitive
Learning with Application to Kernelbased Clustering", Pattern Recognition, Vol. 47, pp. 30603069, 2014.
[J.020] M. Lutf, X.G. You, Y.M.
Cheung and C.L. Philip Chen, “Arabic Font
Recognition Based on Diacritics Features”, Pattern Recognition, Vol. 47, No. 2, pp. 672684, 2014.
[J.019] Y.M. Cheung and
H. Jia, "Categoricalandnumericalattribute
Data Clustering based on a Unified Similarity Metric without Knowing Cluster
Number", Pattern Recognition,
Vol. 46, No. 8, pp. 22282238, 2013. [Source
Code (zip)]
[J.018] H.
Zeng and Y.M. Cheung, "Semisupervised Maximum
Margin Clustering with Pairwise Constraints", IEEE Transactions on
Knowledge and Data Engineering, Vol. 24, No. 5, pp. 926939, 2012.
[J.017] Y.M. Cheung, X. Liu and X.G. You, "A Local Region Based
Approach to Lip Tracking", Pattern Recognition, Vol. 45, No. 9, pp. 33363347, 2012.
[J.016] H.
Zeng and Y.M. Cheung, "Feature
Selection and Kernel Learning for Local LearningBased Clustering", IEEE
Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 8,
pp. 15321547, August 2011.
[J.015] X.G.
You, L. Du, Y.M. Cheung and Q.H. Chen, "A Blind
Watermarking Scheme Using New Nontensor Product Wavelet Filter Banks",
IEEE Transactions on Image Processing, Vol. 19, No. 12, pp. 32713284,
2010.
[J.014] Y.
Liu, Mark Li, Y.M. Cheung, Pak C. Sham and Michael K. Ng, "SKMSNP: SNP
Markers Detection Method", Journal of Biomedical Informatics,
Vol. 43, No. 2, pp. 233239, 2010.
[J.013] H.T.
Wu and Y.M. Cheung, "Reversible
Watermarking by Modulation and Security Enhancement", IEEE
Transactions on Instrumentation and Measurement, Vol. 59, No. 1, pp.
221228, 2010.
[J.012] Y.M. Cheung and H. Zeng, "Local
Kernel Regression Score for Selecting Features of Highdimensional Data",
IEEE Transactions on Knowledge and Data Engineering, Vol. 21, No. 12,
pp. 17981802, 2009.
[J.011] H.
Zeng and Y.M. Cheung, "A New Feature
Selection Method for Gaussian Mixture Clustering", Pattern
Recognition, Vol. 42, No. 2, pp. 243250, 2009.
[J.010] Mark
J. Li, Michael K. Ng, Y.M. Cheung and Joshua Z.X. Huang, "Agglomerative Fuzzy
KMeans Clustering Algorithm with Selection of Number of Clusters", IEEE
Transactions on Knowledge and Data Engineering, Vol. 20, No. 11, pp.
15191534, 2008.
[J.009] 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. 10071016, 2007.
[J.008] 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.
14291434, 2006.
[J.007] 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. 750761, 2005. [Source Code (zip)]
[J.006] 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. 15831588, 2005.
[J.005] 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.
10191028, October, 2005.
[J.004] Y.M. Cheung , "k*Means: A New
Generalized kMeans Clustering Algorithm", Pattern Recognition
Letters, Vol. 24, Issue 15, pp. 28832893, 2003.
[J.003] Y.M. Cheung and L. Xu, "Dual
Multivariate Autoregressive Modeling in State Space for Temporal Signal
Separation", IEEE Transactions on Systems, Man and Cybernetics Part
B: Cybernetics, Vol. 33, No. 3, pp. 386398, June, 2003.
[J.002] 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. 413425, March, 2003.
[J.001] Y.M. Cheung and L. Xu, "An RPCLbased
Approach for Markov Model Identification with Unknown State
Number", IEEE Signal Processing Letters, Vol. 7, No. 10, pp.
284287, October, 2000.
II. Selected Refereed
Conference Papers (Sorted by Reverse Chronological Order)
[C.039] J. Lou and Y.M. Cheung, “Uplink Communication Efficient
Differentially Private Sparse Optimization with Featurewise Distributed Data”,
Proceedings of the Thirtysecond AAAI
Conference on Artificial Intelligence (AAAI’2018), pp. 125133, New
Orleans, Louisiana, USA, February 27, 2018 [Paper].
[C.038] M.
Pang, Y.M. Cheung, B.H. Wang and R.S. Liu, “Robust Heterogeneous Discriminative
Analysis for Single Sample Per Person Face
Recognition”, Proceedings of the 26^{th}
ACM International Conference on Information and Knowledge Management
(CIKM’17), pp. 22512254, Singapore, November 610, 2017. [Paper]
[C.037] Q.Q. Shi, H.P. Lu and Y.M. Cheung, “Tensor Rank
Estimation and Completion via CPbased Nuclear Norm”, Proceedings of the 26^{th} ACM International Conference on
Information and Knowledge Management (CIKM’17), pp. 949958, Singapore,
November 610, 2017.
[Paper, Source Code (zip)]
[C.036] Q.Q.
Shi, Y.M. Cheung and Q.B. Zhao, “Feature Extraction for Incomplete Data via
Lowrank Tucker Decomposition”, Proceedings
of the European Conference on Machine Learning and Principles and Practice of
Knowledge Discovery in Databases (ECMLPKDD’2017), pp. 564581, Skopje,
Macedonia, September 1822, 2017. [Paper, Source Code (zip)]
[C.035] Y.
Lu, Y.M. Cheung and Y.Y. Tang,
“Dynamic Weighted Majority for Incremental Learning of Imbalanced Data Streams
with Concept Drift”, Proceedings of the
26^{th} International Joint Conference on Artificial Intelligence
(IJCAI’2017), pp. 23932399, Melbourne, Australia, August 1925, 2017. [Paper, Source Code (zip)]
[C.034] Y. Zhou, H.P. Lu and Y.M.
Cheung, “Bilinear Probabilistic Canonical Correlation Analysis via Hybrid
Concatenations”, Proceedings of the
Thirtyfirst AAAI Conference on Artificial Intelligence (AAAI’2017), pp. 29492955, San Francisco,
California USA, February 49, 2017. [Paper]
[C.032] Y.M.
Cheung and J. Lou, “Scalable Spectral kSupport Norm Regularization for
Robust Low Rank Subspace Learning”, Proceedings
of the 25^{th} ACM International Conference on Information and
Knowledge Management (CIKM’2016), pp. 11511160, Indianapolis, USA, October
2428, 2016, DOI: http://dx.doi.org/10.1145/2983323.2983738 [Paper, Experimental Code].
[C.031] H.F. Huang, H. Zhang and Y.M.
Cheung, “The Common SelfPolar Triangle of Separate Circles: Properties and
Applications to Camera Calibration”, Proceedings
of IEEE International Conference on Image Processing (ICIP’2016), pp.
11701174, Phoenix, Arizona, USA, September 2528, 2016. [Paper]
[C.030] Y. Lu, Y.M.
Cheung and Y.Y. Tang, “Hybrid Sampling with Bagging for Class Imbalance
Learning”, Proceedings of the 20^{th}
PacificAsia Conference on Knowledge Discovery and Data Mining (PAKDD’2016), LNAI 9651,
Part I, pp. 1426, Auckland, New Zealand, April 1922, 2016. [Paper]
[C.029] H.F. Huang, H. Zhang and Y.M. Cheung, “Homography Estimation from the Common Selfpolar Triangle
of Separate Ellipses”, Proceedings of 2016 IEEE Conference on Computer Vision
and Pattern Recognition (CVPR’2016), pp. 17371744, 2016. [Paper]
[C.028] Y.M. Cheung and J. Lou, “Efficient Generalized Conditional
Gradient with Gradient Sliding for Composite Optimization”, Proceedings of the TwentyFourth
International Joint Conference on Artificial Intelligence (IJCAI’2015), pp.
34093415, 2015.
[Paper]
[C.027] H.F. Huang, H. Zhang and Y.M. Cheung, “The Common Selfpolar Triangle of Concentric Circles
and Its Application to Camera Calibration”, Proceedings
of the IEEE Conference on Computer Vision and Pattern Recognition
(CVPR’2015), pp. 40654072, 2015. [Paper]
[C.026] Y.M. Cheung and J. Lou, “Proximal Average Approximated
Incremental Gradient Method for Composite Penalty Regularized Empirical Risk
Minimization”, JMLR: Workshop and
Conference Proceedings of the 7^{th}
Asian Conference on Machine Learning (ACML’2015), 45, pp. 205220, Hong
Kong, November 2022, 2015.
[Paper]
[C.025] Z.Q. Zhao,
B.J. Xie, Y.M. Cheung and X.D. Wu, “Plant
Leaf Identification via A Growing Convolution Neural Network with Progressive
Sample Learning”,
Proceedings of the 12^{th} Asian
Conference on Computer Vision (ACCV’14), Part II, LNCS 9004, pp. 348361,
Singapore, November 15, 2014.
[C.024] H.F. Huang, H. Zhang and Y.M. Cheung, “Camera Calibration Based on the Common Selfpolar
Triangle of Sphere Images”, Proceedings
of the 12^{th} Asian Conference on Computer Vision (ACCV’14), Part
II, LNCS 9004, pp. 1929, Singapore, November 15, 2014. [Paper]
[C.023] J.
Wang, Z.Q. Zhao, X.G. Hu, Y.M. Cheung,
M. Wang and X.D. Wu, “Online Group Feature Selection”, Proceedings of the 23^{rd} International Joint Conference on
Artificial Intelligence (IJCAI’2013), pp. 17571763, Beijing,
August 2013. [Paper]
[C.022] Y.M.
Cheung and H. Jia, “A Unified Metric for Categorical and Numerical
Attributes in Data Clustering”, Proceedings
of the 17^{th} PacificAsia Conference on Knowledge Discovery and Data
Mining (PAKDD’2013), Vol. 2, LNAI 7819, pp. 135146,
April 1417, Gold Coast, Australia, 2013.
[C.021] X. Liu
and Y.M. Cheung, “A Multiboosted
HMM Approach to Lip Password Based Speaker Verification”, Proceedings of 2012 IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP’2012), pp. 21972200, Kyoto, Japan, March
2530, 2012.
[C.020] S.J. Peng, X. Liu and Y.M. Cheung, “Subspace Based Active Contours with a Joint
Distribution Metric for Semisupervised Natural Image Segmentation”, Proceedings of 2012 IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP’2012), pp.
11731176, Kyoto, Japan, March 2530, 2012.
[C.019] Y.M.
Cheung and M. Li, “MAPMRF Based Lip Segmentation without True
Segment Number”, Proceedings of 19^{th}
IEEE International Conference on Image Processing
(ICIP’11), pp. 781784, September 1114, 2011.
[C.018]
X.
Liu and Y.M. Cheung, "A Robust Lip Tracking Algorithm Using
Localized Color Active Contours and Deformable Models", Proceedings of
2011 International Conference on Acoustics, Speech and Signal Processing
(ICASSP'11), pp. 11971200, 2011. [Paper]
[C.017]
S.J.
Peng, X. Liu and Y.M. Cheung,
“Active Contours with a Novel Distribution Metric for Complex Object
Segmentation”, Proceedings of 19^{th}
IEEE International Conference on Image Processing
(ICIP’11), pp. 34063409, September 1114, 2011.
[C.016] Y.M. Cheung and H. Jia, "A
Cooperative and Penalized Competitive Learning Approach to Gaussian Mixture
Clustering", Proceedings of the 20th International Conference on
Artificial Neural Networks (ICANN'10), Lecture Notes in Computer Science
(LNCS 6354), pp. 435440, 2010. [Paper]
[C.015]
M.
Li and Y.M. Cheung, "Automatic Segmentation of Color Lip Images
Based on Morphological Filter", Proceedings of the 20th International
Conference on Artificial Neural Networks (ICANN'10), Lecture Notes in
Computer Science (LNCS 6352), pp. 384387, 2010. [Paper]
[C.014]
X.
Liu, Y.M. Cheung, M. Li and H.L. Liu, "A Lip Contour Extraction
Method Using Localized Active Contour Model with Automatic Parameter
Selection", Proceedings of 2010 International Conference on Pattern
Recognition (ICPR'2010), pp. 43324335, 2010. [Paper]
[C.013] Q.M.
Peng, X.G. You, L. Zhou and Y.M. Cheung, "Retinal
Blood Vessels Segmentation Using the Radial Projection and Supervised
Classification",
Proceedings of 2010 International Conference on Pattern Recognition
(ICPR'2010), pp. 14891492, 2010. [Paper]
[C.012]
P.
Winoto and Y.M. Cheung and J.M. Liu, "Mechanism Design for
Clustering Aggregation by Selfish Systems", Proceedings of 7th IEEE
International Conference on Data Mining (ICDM'07), pp. 703708, 2007. [Paper]
[C.011] Y.M. Cheung and H. Zeng, "A
Maximum Weighted Likelihood Approach to Simultaneous Model
Selection and Feature Weighting in Gaussian Mixture", Proceedings of
2007 International Conference on Artificial Neural Networks (ICANN'07),
LNCS 4668, Part I: pp. 7887, 2007. [Paper]
[C.010] H.T. Wu and Y.M. Cheung,
"A HighCapacity Data Hiding Method for Polygonal Meshes", Proceedings
of 8th Information Hiding (IH'06), 2006. [Paper]
[C.009] H.T. Wu and Y.M. Cheung, "A Fragile Watermarking
Scheme for 3D
Meshes", Proceedings of the 7th Workshop on Multimedia & Security
(ACM'05), pp. 117123, 2005.
[Paper]
[C.008] 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. 472477, Chongqin, 2005. [Paper]
[C.007] 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. 633636, Cambridge, United Kingdom,
2004.
[Paper]
[C.006] Y.M.
Cheung, "A Competitive and Cooperative Learning Approach to
Robust Data Clustering", Proceedings of the IASTED International Conference
on Neural Networks and Computational Intelligence (NCI'2004), pp. 131136, Grindelwald, Switzerland, 2004. [Paper]
[C.005] 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. 137141, Grindelwald,
Switzerland, 2004.
[Paper]
[C.004] Y.M. Cheung and R.B. Huang, "An
Advance on DivideandConquer Based Radial Basis Function Networks", Proceedings
of Fourth International Conference on Intelligent Data Engineering and
Automated Learning (IDEAL'2003), pp. 143150, Springer Publisher, Hong
Kong, March 2123, 2003. [Paper]
[C.003]
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 2024, 2003. [Paper]
[C.002] 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 CDROM Proceeding), Singapore,
November 1822, 2002. [Paper]
[C.001] Y.M. Cheung, "A New Recurrent Radial Basis Function Network", Proceedings of 9th International Conference on Neural Information Processing (Paper ID: 1538 in CDROM Proceeding) , Singapore, November 1822, 2002. [Paper]
Book Chapter:
[B.001] Z.B. Lai, Y.M. Cheung and L. Xu, "Independent Component Ordering in ICA Analysis of Financial Data", Computational Finance, Chapter 14, pp. 201212, edited by Yaser S. AbuMostafa, Blake LeBaron, Andrew W. Lo and Andreas S. Weigend, The MIT Press, 1999.
CoEdited 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.
List of Taught Courses:
COMP2230 / COMP3005
Design and Analyis of Algorithms
COMP7640 Database Systems &
Administration
COMP1170
Introduction to Structured Programming
COMP
1210 /
COMP 2015 Data Structures and Algorithms
COMP
2440 Database Systems II
COMP3010
Artificial Intelligence
COMP3170
Artificial Intelligence and Machine Learning
SCI3790
Machine Learning: Theories & Applications
SCI 4150 Artificial Intelligence (M.Sc. Course)