• W. Ching and M. Ng, Basic Elements and Models of Management Mathematics, GBS Publishers (2007), 230 pages
• T. Park, S. Tsui, L. Chen, M. Ng, L. Wong, X. Hu: 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010, Hong Kong, China, 18 - 21 December 2010, Proceedings IEEE Computer Society 2010 [ISBN 978-1-4244-8305-1]
• W. Liu, M. Ng and Z. Shi, Recent Progress in Scientific Computing, Science Press (2007), 401 pages [ISBN 978-7-03-019043-7]
• W. Ching and M. Ng, Markov Chains: Models, Algorithms and Applications, International Series on Operations Research and Management Science, Springer (2006), 205 pages [ISBN 0-387-29335-3]
• M. Ng, A. Doncescu, L. Yang and T. Leng, High Performance Computational Science and Engineering, IFIP TC5 Workshop on High Performance Computational Science and Engineering, Springer (2005), 238 pages [ISBN 0-387-24048-9]
• M. Ng, Iterative Methods for Toeplitz Systems, Oxford University Press (2004), 360 pages [ISBN 0-19-850420-9]
• W. Ching and M. Ng, Advances in Data Mining and Modeling, World Scientific Press (2003), 181 pages. ISBN 981-238-354-9.
• J. Fong and M. Ng, The Fifth Pacific-Asia Conference on Knowledge Discovery and Data Mining, Industrial Track and Workshops Proceeding, Printed by the the City University of Hong Kong, 2001. ISBN 962-442-187-0.

• Numerical Linear Algebra with Applications: The Special Issue for Dedication to Robert J. Plemmons, 2015.
• Numerical Linear Algebra with Applications: The Special Issue of the Spectral Theory of Tensors and Its Applications, Volume 20(6), 2013.
• IEEE/ACM Transactions on Computational Biology and Bioinformatics: Guest Editorial: Bioinformatics and Computational Systems Biology, Volume 9(4), pp. 945-946, 2012.
• Numerical Linear Algebra with Applications: The Special Issue for the 3rd International Conference on Structured Matrices and Tensors, Volume 19(1), 2012.
• Journal of Computational Mathematics: The Special Issue for Joint China-Russia Conference on Computational Mathematics, Volumes 29(6) 2011, and 30(1), 2012.
• Numerical Mathematics: Theory, Methods and Applications: Special Issue for Image Processing and Numerical Linear Algebra, Volume 2, No. 4, 2009
• Linear Algebra and Its Applications: The Special Issue on Structured Matrices, Volume 428, Issues 2+3, 2008
• Multidimensional Systems and Signal Processing: Special Issue on Superresolution Imaging: Theory, Algorithms and Applications, Volume 18, Number 2/3, 2007
• Journal of Computational Mathematics: The Summer Workshop on Numerical Linear Algebra (2005), Volume 25, Number 5, 2007
• EURASIP Journal on Advances in Signal Processing: Super-Resolution Imaging: Analysis, Algorithms and Applications, Volume 2006, 2006
• Numerical Linear Algebra with Applications: Special Issue: Structured Matrices with Applications, Volume 12, Issue No. 2-3, 2005
• International Journal of Imaging Systems and Technology: The Special Issue: High-Resolution Imaging Reconstruction I and II, Volume 14, Nos. 2 and 3, 2004
• International Journal of Applied Mathematics: ``OR and Models'', Volume 13, No. 1, 2003

(Numerical Linear Algebra):

• W. Li, D. Liu, M. Ng, S. Vong, The Bounds for Uniqueness of Multilinear PageRank Vector, Numerical Linear Algebra with Applications
• X. Lin, M. Ng and H. Sun, A Multigrid Method for Linear Systems Arising from Time-Dependent Two-Dimensional Space-Fractional Diffusion Equations, Journal of Computational Physics, V336 (2017), pp. 69-86
• V. Rao, A. Sandu, M. Ng and E. Nino-Ruiz, Robust Data Assimilation Using L1 and Huber Norms, SIAM Journal on Scientific Computing
• H. Fu, M. Mg and H. Wang, A Divide-and-conquer Fast Finite Fifference Method for Space-time Fractional Partial Differential Equation, Computers and Mathematics with Applications, V73 (2017), pp. 1233-1242
• C. Chuan, M. Ng and S. Zhang, Block Spectral Clustering Methods for Multiple Graphs, Numerical Linear Algebra with Applications, V24 (2017)
• J. Pan, M. Ng and H. Wang, Fast Preconditioned Iterative Methods for Finite Volume Discretization of Steady-State Space-fractional Diffusion Equations, Numerical Algorithms, V74 (2017), pp. 153-173
• R. Ke, W. Li and M. Ng, Numerical Ranges of Tensors, Linear Algebra and its Applications, V508 (2016), pp. 100-132
• J. Pan, M. Ng and H. Wang, Fast Iterative Solvers for Linear Systems Arising from Time-Dependent Space-Fractional Diffusion Equations, SIAM Journal on Scientific Computing, V38 (2016), pp. 2806-2826
• X. Zhang, L. Cheng, D. Chu, L. Liao, M. Ng and R. Tan, Incremental Regularized Least Squares for Dimensionality Reduction of Large-scale Data, SIAM Journal on Scientific Computing, V38 (2016), pp. 414-439
• L. Cui, C. Chen, W. Li and M. Ng, An Eigenvalue Problem for Even Order Tensors with its Applications, Linear and Multilinear Algebra, V64 (2016)
• C. Chen, X. Li, M. Ng and X. Yuan, Total Variation Based Tensor Decomposition for Multi-Dimensional Data with Time Dimension, Numerical Linear Algebra with Applications, V22 (2015), pp. 999-1019
• L. Cui, W. Li and M. Ng, Primitive Tensors and Directed Hypergraphs, Linear Algebra and its Applications, V471 (2015), pp. 96-108
• W. Li and M. Ng, The Perturbation Bound for the Spectral Radius of a Nonnegative Tensor, Advances in Numerical Analysis, Volume 2014 (2014), Article ID 109525
• W. Li and M. Ng, Some Bounds for the Spectral Radius of Nonnegative Tensors, Numerische Mathematik, V130 (2015), pp. 315-335
• X. Li and M. Ng, Solving Sparse Non-Negative Tensor Equations: Algorithms and Applications, Frontiers of Mathematics in China, V10 (2015), pp. 649-680
• Q. Niu and M. Ng, Numerical Studies of a Class of Composite Preconditioners, Journal of Computational Mathematics, V32 (2014), pp. 136-151
• J. Pan, R. Ke, M. Ng and H. Sun, Preconditioning Techniques for Diagonal-Times-Toeplitz Matrices in Fractional Diffusion Equations, SIAM Journal on Scientific Computing, V36 (2014), pp. 2698-2719
• L. Cui, W. Li and M, Ng, Birkhoff-von Neumann Theorem for Multi-Stochastic Tensors, SIAM Journal on Matrix Analysis and Applications, V35 (2014), pp. 956-973
• X. Chen, W. Li and M. Ng, On Condition Numbers of the Spectral Projections Associated with Periodic Eigenproblems, Journal of Computational and Applied Mathematics, V272 (2014), pp. 417-429
• W. Li, L. Cui and M. Ng, The Perturbation Bound for the Perron Vector of a Transition Probability Tensor, Numerical Linear Algebra with Applications, V20 (2013), pp. 985-1000
• W. Li and M. Ng, On the Limiting Probability Distribution of a Transition Probability Tensor, Linear and Multilinear Algebra, V62 (2014), pp. 362-385
• D. Chu, L. Liao and M. Ng, Sparse Orthogonal Linear Discriminant Analysis, SIAM Journal on Scientific Computing, V34 (2012), pp. 2421-2443
• W. Li, M. Ng and L. Cui, On Computation of the Steady-State Probability Distribution of Probabilistic Boolean Networks with Gene Perturbation, Journal of Computational and Applied Mathematics, V236 (2012), pp. 4067-4081
• X. Chen, W. Li and M. Ng, Perturbation Analysis for Anti-triangular Schur Decomposition, SIAM Journal on Matrix Analysis and Applications, V33 (2012), pp. 325-335
• G. Yin, J. Yin and M. Ng, On Adaptively Accelerated Arnoldi Method for Computing PageRank, Numerical Linear Algebra with Applications, V19 (2012), pp. 73-85
• L. Zhang, L. Liao and M. Ng, Superlinear Convergence of a General Algorithm for the Generalized Foley-Sammon Discriminant Analysis, Journal of Optimization Theory and Applications, V157 (2013), pp. 853-865
• Y. Wen, W. Ching and M. Ng, Approximate Inverse-Free Preconditioners for Toeplitz Matrices, Applied Mathematics and Computation, V217 (2011), pp. 6856-6867
• N. Mastronardi, M. Ng, E. Tyrtyshnikov, Decay in Functions of Multi-band Matrices, SIAM Journal on Matrix Analysis and Applications, V31 (2010), pp. 2721-2737
• M. Ng and J. Pan, Approximate Inverse Circulant-plus-Diagonal Preconditioners for Toeplitz-plus-Diagonal Matrices, SIAM Journal on Scientific Computing, V32 (2010), pp. 1442-1464
• Y. Huang and M. Ng, Product-Type Block Preconditioners for Electromagnetic Cavity Problems, Applied Mathematics and Computation, V216 (2010), pp. 1741-1751
• L. Zhang, L. Liao and M. Ng, Fast Algorithms for the Generalized Foley-Sammon Discriminant Analysis, SIAM Journal on Matrix Analysis and Applications, V31 (2010), pp. 1584-1605
• F. Lin and M. Ng, Inverse Product Toeplitz Preconditioners for non-Hermitian Toeplitz Systems, Numerical Algorithms, V54 (2010), pp. 279-295
• M. Ng, L. Qi and G. Zhou, Finding the Largest Eigenvalue of a Non-Negative Tensor, SIAM Journal on Matrix Analysis and Applications, V31 (2009), pp. 1090-1099
• Z. Bai, M. Ng and Z. Wang, Constraint Preconditioners for Symmetric Indefinite Matrices, SIAM Journal on Matrix Analysis and Applications, V31 (2009), pp. 410-433
• L. Chan, M. Ng and N. Tsing, Spectral Analysis for HSS Preconditioners, Numerical Mathematics: Theory, Methods and Applications, V1 (2008), pp. 57-77
• W. Ching, M. Ng and E. Fung, Higher-order Multivariate Markov Chains and their Applications, Linear Algebra and Its Applications, V428 (2008), pp. 492-507
• Z. Bai, G. Golub and M. Ng, On Inexact Hermitian and Skew-Hermitian Splitting Methods for Non-Hermitian Positive Definite Linear Systems, Linear Algebra and Its Applications, V428 (2008), pp. 413-440
• W. Ching, M. Ng and W. Youwei, Block Diagonal and Schur Complement Preconditioners for Block Toeplitz Systems with Small Size Blocks, SIAM Journal on Matrix Analysis and Applications, V29 (2007), pp. 1101-1119
• Y. Wei, N. Zhang, M. Ng and W. Xu, Tikhonov Regularization for Weighted Total Least Squares Problems, Applied Mathematics Letters, V20 (2007), pp. 82-87
• L. Lu and M. Ng, Maximum Inverse Positive Matrices, Applied Mathematics Letters, V20 (2007), pp. 65-69
• Z. Bai, G. Golub and M. Ng, On Successive-Overrelaxation Acceleration of the Hermitian and Skew-Hermitian Splitting Iterations, Numerical Linear Algebra with Applications, V14 (2007), pp. 319-335
• M. Benzi and M. Ng, Preconditioned Iterative Methods for Weighted Toeplitz Least Squares Problems, SIAM J. Matrix Analysis and Applications, V27 (2006), pp. 1106-1124
• J. Cai, M. Ng and Y. Wei, Computing the Group Inverse of Singular Toeplitz Matrix, Journal of Computational Mathematics, V24 (2006), pp. 647-656
• J. Pan, M. Ng and Z. Bai, New Preconditioners for Saddle Point Problems, Applied Mathematics and Computation, V172 (2006), pp. 762-771
• W. Ching, M. Ng and W. Yuen, A Direct Method for Solving Block-Toeplitz with Near-Circulant-Block Systems with Applications to Hybrid Manufacturing Systems, Numerical Linear Algebra with Applications, V12 (2005), pp. 957-966
• L. Lu and M. Ng, Effects of a Parameter on a Nonsymmetric Algebraic Riccati Equation, Applied Mathematics and Computation, V172 (2006), pp. 753-761
• M. Ho and M. Ng, Splitting Iterations for Circulant-plus-diagonal Systems, Numerical Linear Algebra with Applications, V12 (2005), pp. 779-792
• Y. Wei, H. Diao and M. Ng, On Drazin Inverse of Singular Toeplitz Matrix, Applied Mathematics and Computation, V172 (2006), pp. 809-817
• Z. Bai and M. Ng, On Inexact Preconditioners for Nonsymmetric Matrices, SIAM Journal on Scientific Computing, V26 (2005), pp. 1710-1724
• A. Ho and M .Ng, Iterative Methods for Robbins Problems, Applied Mathematics and Computation, V165 (2005), pp. 103-125
• M. He, L. Lu and M. Ng, Toeplitz and Positive Semidefinite Complete Problem for Cycle Graph, Numer. Math.,  J. Chinese Univs., V14 (2005), pp. 67-78
• M. Ng, S. Serra and C. Tablino-Possio, Multigrid Methods for Symmetric Sinc-Galerkin Systems, Numerical Linear Algebra with Applications, V12 (2005), pp. 261-269
• F. Lin, M. Ng and W. Ching, Factorized Banded Inverse Preconditioners for Matrices with Toeplitz Structure, SIAM Journal on Scientific Computing, V26 (2005) pp. 1852-1870
• Y. Wei and M. Ng, Displacement Structure of Group Inverses, Numerical Linear Algebra with Applications, V12 (2005), pp. 103-110
• M. Ng, Stefano Serra-Capizzano and Cristina Tablino-Possio, Multigrid Preconditioners for Symmetric Sinc Systems, ANZIAM J. V45(E), 2004, pp. 857-869
• Y. Wen, M. Ng, W. Ching, H. Liu, A Note on the Stability of Toeplitz Matrix Inversion Formulas, Applied Mathematics Letter, V17 (2004), pp. 903-907
• W. Ching, W. Yuen and M. Ng, A Hybrid Algorithm for Queueing Systems, CALCOLO, V41 (2004), pp. 139-151
• L. Lu, W. Ching and M. Ng, Exact Algorithms for Singular Tridiagonal Systems with Applications to Markov Chains, Applied Mathematics and Computation, V159 (2004) pp. 275-289
• L. Lu and M. Ng, Localization of Perron Roots, Linear Algebra and its Applications, V392 (2004), pp. 103-117
• L. Lu and M. Ng, On Sufficient and Necessary Conditions for the Jacobi Matrix Inverse Eigenvalue Problem, Numer. Math., V98 (2004), pp. 167-176
• Y. Wei and M. Ng, Weighted Tikhonov Filter Matrices for Ill-Posed Problems, Applied Mathematics and Computation, V149 (2004), pp. 411-422
• Y. Wei, J. Cai and M. Ng, Computing Moore-Penrose Inverses of Toeplitz Matrices by Newton's Iteration, Mathematical and Computer Modeling, V40 (2004), pp. 181-191
• L. Lu and M. Ng, Symmetric Versions of Sign-Function Algoriothm for Discrete-time Algebraic Riccati Equations, International Journal of Applied Mathematics, V13 (2003), pp. 100-119
• F. Lin, W. Ching and M. Ng, Accurate and Fast Inversion Methods for Triangular Toeplitz Matrices, Theoretical Computer Science, V43 (2003), pp. 901-914
• F. Lin, W. Ching and M. Ng, Discrete Wavelet Transforms for Toeplitz Matrices, Linear Algebra Appls., V370 (2003), pp. 269-285
• Z. Bai, G. Golub and M. Ng, Hermitian and Skew-Hermitian Splitting Methods for Non-Hermitian Positive Definite Linear Systems, SIAM Journal on Matrix Analysis and Applications, V24 (2003), pp. 603-626
• M. Ng, X. Jin and H. Sun, Recursive-Based PCG Methods for Toeplitz Systems with Nonnegative Generating Functions, SIAM Journal on Scientific Computing, V24 (2003), pp. 1507-1529
• M. Ng, Circulant and Skew-Circulant Splitting Methods for Toeplitz Systems, Journal of Computational Applied Math., V159 (2003), pp. 101-108
• Y. Wen, W. Ching and M. Ng, Explicit Preconditioners for Toeplitz Systems, International Journal of Applied Mathematics, V13 (2003), pp. 72-83
• Z. Bai and M. Ng, Preconditioners for Nonsymmetric Block-Toeplitz-Like-Plus-Diagonal Linear System, Numer. Math., V96 (2003), pp. 197-220
• M. Ng and Z. Bai, A Hybrid Preconditioner of Banded Matrix Approximation and Alternating Direction Implicit Iteration for Symmetric Sinc-Galerkin Linear Systems, Linear Algebra Appls., V366 (2003), pp. 317-335
• M. Ng and D. Potts, Fast Iterative Methods for Sinc Systems, SIAM Journal on Matrix Analysis and Applications, V24 (2003), pp. 581-598
• M. Ng, K. Rost and Y. Wen, On Inversion of Toeplitz Matrices, Linear Alg. and Applications, V348 (2002), pp. 145-151
• R. Chan, M. Ng and A. Yip, The Best Circulant Preconditioners for Hermitian Toeplitz Systems II: The Multiple-Zero Case, Numer. Math., V92 (2002), pp. 17-40
• M. Ng and D. Potts, Circulant Preconditioners for Indefinite Toeplitz Systems, BIT, V41 (2001), pp. 1079-1088
• R. Chan, A. Yip and M. Ng, The Best Circulant Preconditioners for Hermitian Toeplitz Matrices, SIAM Journal on Numerical Analysis, V38 (2001), pp. 876-896
• M. Ng, Preconditioned Lanczos Methods for the Minimum Eigenvalue of a Symmetric Positive Definite Toeplitz Matrix, SIAM Journal on Scientific Computing, V21 (2000), pp. 1973-1986
• T. Chan and M. Ng, Galerkin Projection Methods for Solving Multiple Linear Systems, SIAM Journal on Scientific Computing, V21 (2000), pp. 836-850
• M. Ng, Fast Iterative Methods for Symmetric Sinc-Galerkin Systems, IMA Journal of Numerical Analysis, V19 (1999), pp. 357-373
• H. Chan, M. Ng and R. Chan, Band Toeplitz Preconditioners for Toeplitz Systems with Rational Generating Functions, The Bulletin of Hong Kong Mathematical Society, V1 (1997), pp. 67-86
• M. Ng, Band Preconditioners for Block-Toeplitz-Toeplitz-Block Systems, Linear Algebra and its Applications, V259 (1997), pp. 307-327
• R. Chan and M. Ng, Scientific Applications of Iterative Toeplitz Solvers, CALCOLO, V33 (1996), pp. 249-267
• R. Chan and M. Ng, Conjugate Gradient Methods for Toeplitz Systems, SIAM Review, V38 (1996), pp. 427-482
• R. Chan, C. Wong and M. Ng, Sine-transform Based Preconditioners For Symmetric Toeplitz Systems, Linear Algebra and its Applications, V232 (1996), pp. 237-259
• R. Chan and M. Ng, Toeplitz Preconditioners for Hermitian Toeplitz Systems, Linear Algebra and its Applications, V190 (1993), pp. 181-208
• R. Chan and M. Ng, Fast Iterative Solver for Toeplitz-plus-Band Systems, SIAM Journal on Scientific Computing, V14 (1993), pp. 1013-1019

• M. Ng, H. Ngan, X. Yuan and W. Zhang, Lattice-based Patterned Fabric Inspection by Using Total Variation with Sparsity and Low-Rank Representations, SIAM Journal on Imaging Sciences
• X. Li, M. Ng, Y. Ye, E. Wang and X. Xu, Block Linear Discriminant Analysis for Visual Tensor Objects with Frequency or Time Information, Journal of Visual Communication and Image Representation
• L. Jing, C. Shen, L. Yang, J. Yu and M. Ng, Multi-label Classification by Semi-supervised Singular Value Decomposition, IEEE Transactions on Image Processing
• X. Zhang, M. Bai and M. Ng, Nonconvex-TV Based Image Restoration with Impulse Noise Removal, SIAM Journal on Imaging Sciences
• W. Wei, X. Zhao and M. Ng, A Variational Approach for Restoring Images Corrupted by Noisy Blur Kernels and Additive Noise, Numerical Linear Algebra with Applications
• M. Ng, Q. Yuan, L. Yan and J. Sun, An Adaptive Weighted Tensor Completion Method for the Recovery of Remote Sensing Images With Missing Data, IEEE Transactions on Geoscience and Remote Sensing
• X. Zhang, B. Javidi, M. Ng, Automatic Regularization Parameter Selection by Generalized Cross-validation for Total Variational Poisson Noise Removal, Applied Optics, V56 (2017), pp. D47-D51
• L. Pi, W. Wang and M. Ng, A Spatially Variant Total Variational Model for Chromatic Aberration Correction, Journal of Visual Communication and Image Representation, V41 (2016), pp. 296-304
• H. Chang, Y. Lou, M. Ng and T. Zeng, Phase Retrieval from Incomplete Magnitude Information via Total Variation Regularization, SIAM Journal on Scientific Computing, V38 (2016), pp. 3672-3695
• W. Wei and M. Ng, Convex Regularized Inverse Filtering Methods for Blind Image Deconvolution, Signal, Image and Video Processing, V10 (2016), pp. 1353-1360
• W. Fan, X. Zhao and M. Ng, Multiplicative Noise and Blur Removal by Framelet Decomposition and l1-based L-curve Method, IEEE Transactions on Image Processing, V25 (2016), pp. 4222-4232
• L. Yang, M. Ng, J. Yu and L. Jing, A Discriminative and Sparse Topic Model for Image Classification and Annotation, Image and Vision Computing, V51 (2016), pp. 22-35
• Z. Jin, C. Zhou and M. Ng, A Coupled Total Variation Model with Curvature Driven for Image Colorization, Inverse Problems and Imaging, V10 (2016), pp. 1037-1055
• X. Li, M. Ng and Y. Ye, MultiVCRank with Applications to Image Retrieval, IEEE Transactions on Image Processing, V25 (2016), pp. 1396-1409
• W. Wang, C. Chen and M. Ng, An Image Pixel Based Variational Model for Histogram Equalization, Journal of Visual Communication and Image Representation, V34 (2016), pp. 118-134
• L. Yang, L. Jing and M. Ng, Robust and Non-Negative Collective Matrix Factorization for Text-to-Image Transfer Learning, IEEE Transactions on Image Processing, V24 (2015), pp. 4701-4714
• X. Li, M. Ng and X. Yuan, Median Filtering Based Methods for Static Background Extraction from Surveillance Video, Numerical Linear Algebra with Applications, V22 (2015), pp. 845-865
• W. Wang, X. Zhao and M. Ng, A Cartoon-plus-Texture Image Decomposition Model for Blind Deconvolution, Multidimensional Systems and Signal Processing, V27 (2016), pp. 541-562
• J. Xiao, M. Ng and Y. Yang On the Convergence of Nonconvex Minimization Methods for Image Recovery, IEEE Transactions on Image Processing, V24 (2015), pp. 1587-1598
• H. Chang, M. Ng, W. Wang, T. Zeng, Retinex Image Enhancement via a Learned Dictionary, Optical Engineering, 54(1) (2015), 013107
• M. Qiao and M. Ng, Tone Mapping for High Dynamic Range Images Using Localized Gamma Correction, Journal of Electronic Imaging, V24 (2015), 013010
• C. Chen, M. Ng and X. Zhao, Alternating Direction Method of Multipliers for Nonlinear Image Restoration Problems, IEEE Transactions on Image Processing, V24 (2015), pp. 33-43
• Z. Jin and M. Ng, A Contrast Maximization Method for Color-to-Grayscale Conversion, Multidimensional Systems and Signal Processing, V26 (2015), pp. 869-877
• M. Ng, H. Ngan, X. Yuan and W. Zhang, Patterned Fabric Inspection and Visualization by the Method of Image Decomposition, IEEE Transactions on Automation Science and Engineering, V11 (2014), pp. 943-947
• W. Wang and M. Ng, A Nonlocal Total Variation Model for Image Decomposition: Illumination and Reflectance, Numerical Mathematics: Theory , Methods and Applications, V7 (2014), pp. 334-355
• Z. Jin, F. Li and M. Ng, A Variational Approach for Image Decolorization By Variance Maximization, SIAM Journal on Imaging Sciences, V7 (2014), pp. 944-968
• M. Ng and J. Pan, Weighted Toeplitz Regularized Least Squares Computation for Image Restoration, SIAM Journal on Scientific Computing, V36 (2014), pp. 94-121
• L. Jing and M. Ng, Sparse Label-Indicator Optimization Methods for Image Classification, IEEE Transactions on Image Processing, V23 (2014), pp. 1002-1014
• X. Zhao, F. Wang and M. Ng, A New Convex Optimization Model for Multiplicative Noise and Blur Removal, SIAM Journal on Imaging Sciences, V7 (2014), pp. 456-475
• H. Chang, M. Ng and T. Zeng, Reducing Artifact in JPEG Decompression via a Learned Dictionary, IEEE Transactions on Signal Processing, V62 (2014), pp. 718-728
• M. Qiao, W. Wang, M. Ng, Multiphase Texture Segmentation Using Gabor Features Histograms Based on Wasserstein Distance, Communications in Computational Physics, V15 (2014), pp. 1480-1500.
• X. Zhao, W. Wang, T. Zeng, T. Huang and M. Ng, Total Variation Structured Total Least Squares Method for Image Restoration, SIAM Journal on Scientific Computing, V35 (2013), pp. 94-121
• W. Wang and M. Ng, A Variational Histogram Equalization Method for Image Contrast Enhancement, SIAM Journal on Imaging Sciences, V6 (2013), pp. 1345-1366
• M. Ng, C. Tam and F. Wang, Multi-view Foreground Segmentation via Fourth Order Tensor Learning, Inverse Problems and Imaging, V7 (2013), pp. 885-906
• M. Ng and W. Wang A Variational Approach for Image Stitching II: Using Image Gradients, SIAM Journal on Imaging Sciences, V6 (2013), pp. 1345-1366
• W. Wang and M. Ng, A Variational Approach for Image Stitching, SIAM Journal on Imaging Sciences, V6 (2013), pp. 1318-1344
• L. Ma, M. Ng, J. Yu and T. Zeng, Efficient Box-Constrained TV-Type-L22 Algorithms for Restoring Images with Impulse Noise, Journal of Computational Mathematics, V31 (2013), pp. 249-270
• M. Ng, X. Yuan and W. Zhang, A Coupled Variational Image Decomposition and Restoration Model for Blurred Cartoon-plus-Texture Images with Missing Pixels, IEEE Transactions on Image Processing, V22 (2013), pp. 2233-2246
• X. Zhao, F. Wang, T. Huang, M. Ng and R. Plemmons, Deblurring and Sparse Unmixing For Hyperspectral Images, IEEE Transactions on Geoscience and Remote Sensing, V51 (2013), pp. 4045-4058
• M. Nikolova, M. Ng and C. Tam, On l_1 Data Fitting and Concave Regularization for Image Recovery, SIAM Journal on Scientific Computing, V35 (2013), pp. 397-430
• X. Chen, M. Ng and C. Zhang, Non-Lipschitz l_p-regularization and Box Constrained Model for Image Restoration, IEEE Transactions on Image Processing, V21 (2012), pp. 4709-4720
• L. Jing, C. Zhang and M. Ng, SNMFCA: Supervised NMF-based Image Classification and Annotation, IEEE Transactions on Image Processing, V21 (2012), pp. 4508-4521
• Y. Huang, L. Moisan, M. Ng and T. Zeng, Multiplicative Noise Removal via a Learned Dictionary, IEEE Transactions on Image Processing, V21 (2012), pp. 4534-4543
• F. Wang and M. Ng, A Fast Minimization Method for Blur and Multiplicative Noise Removal, International Journal of Computer Mathematics, V90 (2013), pp. 48-61
• Y. Law, H. Lee, M. Ng and A. Yip, A Semi-supervised Segmentation Model for Collections of Images, IEEE Transactions on Image Processing, V21 (2012), pp. 2955-2968
• W. Wang and M. Ng, A Variational Method for Blending of Multiple Images, IEEE Transactions on Image Processing, V21 (2012), pp. 1809-1822
• F. Li, M. Ng, R. Plemmons, Coupled Segmentation and Denoising/Deblurring Models for Hyperspectral Material Identification, Numerical Linear Algebra with Applications, V19 (2012), pp. 153-173
• W. Wang and M. Ng, On Algorithms for Automatic Deblurring From a Single Image, Journal of Computational Mathematics, V30 (2012), pp. 80-100
• M. Ng, F. Wang and X. Yuan, Inexact Alternating Direction Methods for Image Recovery, SIAM Journal on Scientific Computing, V33 (2011), pp. 1643-1668
• Y. Xiao, T. Zeng, J. Yu and M. Ng, Restoration of Images Corrupted by Mixed Gaussian-Impulse Noise via l_1-l_0 Minimization, Pattern Recognition, V44 (2011), pp. 1708-1720
• M. Ng and W. Wang, A Total Variation Model for Retinex, SIAM Journal on Imaging Sciences, V4 (2011), pp. 345-365
• H. Liao and M. Ng, Blind Deconvolution Using Generalized Cross Validation Approach to Regularization Parameter Estimation, IEEE Transactions on Image Processing, V20 (2011), pp. 670-680
• M. Ng, F. Wang and X. Yuan, Fast Minimization Methods for Solving Constrained Total-Variation Superresolution Image Reconstruction, Multidimensional Systems and Signal Processing, V22 (2011), pp. 259-286
• A. Yau, X. Tai and M. Ng, Compression and Denoising using l_0-norm, Journal Computational Optimization and Applications V50 (2011), pp. 425-444
• M. Ng, P. Weiss and X. Yuan, Solving Constrained Total-Variation Image Restoration and Reconstruction Problems via Alternating Direction Methods, SIAM Journal on Scientific Computing, V32 (2010), pp. 2710-2736
• F. Li, M. Ng and C. Li, Variational Fuzzy Mumford-Shah Model for Image Segmentation, SIAM Journal on Applied Mathematics, V70 (2010), pp. 2750-2770
• M. Nikolova, M. Ng and C. Tam, Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction, IEEE Transactions on Image Processing, V19 (2010), pp. 3073-3088
• M. Ng, G. Qiu and A. Yip, Numerical Methods for Interactive Multiple Class Image Segmentation Problems, International Journal of Imaging Systems and Technology, V20 (2010), pp. 191-201
• F. Li, M. Ng, T. Zeng and C. Shen, A Multiphase Image Segmentation Method Based on Fuzzy Region Competition, SIAM Journal on Imaging Sciences, V3 (2010), pp. 277-299
• T. Zeng, X. Li and M. Ng, Alternating Minimization Method for Total Variation Based Wavelet Shrinkage Model, Communications in Computational Physics, V8 (2010), pp. 976-994
• M. Poole, P. Weiss, H. Lopez, M. Ng and S. Crozler, Minimax Current Density Coil Design, Journal of Physics D: Applied Physics, V43 (2010), 095001
• K. Wong, C. Tam and M. Ng, Accurate Vascular Delay Estimation from Low Temporal Resolution Image Dataset, IEEE Signal Processing Magazine, V27 (2010), pp. 155-158
• F. Li and M. Ng, Kernel Density Estimation Based Multiphase Fuzzy Region Competition Method for Texture Image Segmentation, Communications in Computational Physics, V8 (2010), pp. 623-641
• Z. Bai, Y. Huang and M. Ng, Block-triangular Preconditioners fro Systems Arising From Edge-preserving Image Restoration, Journal of Computational Mathematics, V28 (2010), pp. 848-847
• Z. Bai, Y. Huang, M. Ng and X. Yang Preconditioned Iterative Methods for Algebraic Systems from Multiplicative Half-Quadratic Regularization Image Restorations, Numer. Math. Theor. Meth. Appl., V3 (2010), pp. 461-474
• F. Li, M. Ng and C. Shen, Multiplicative Noise Removal with Spatial-Varying Regularization Parameters, SIAM Journal on Imaging Sciences, V3 (2010), pp. 1-20
• T. Zeng and M. Ng, On the Total Variation Dictionary Model, IEEE Transactions on Image Processing, V19 (2010), pp. 821-825
• H. Liao, F. Li and M. Ng, On Selection of Regularization Parameter in Total Variation Image Restoration, Journal of the Optical Society of America A, V26 (2009), pp. 2311-2320
• Zheng-Jian Bai, M. Ng and and Liqun Qi, A Coordinate Gradient Descent Method for Nonsmooth Nonseparable Minimization, Numerical Mathematics: Theory, Methods and Applications, V2 (2009), pp. 377-402
• X. Guo, F. Li and M. Ng, A Fast l1-TV Algorithm for Image Restoration, SIAM Journal on Scientific Computing, V31 (2009), pp. 2322-2341
• Y. Huang, M. Ng and Y. Wen, Fast Image Restoration Methods for Impulse and Gaussian Noises Removal, IEEE Signal Processing Letters, V16 (2009), pp. 457-460
• H. Shen, M. Ng, R. Li and L. Zhang, Superresolution Reconstruction Algorithm to MODIS Remote Sensing Images, The Computer Journal, V52 (2009), pp. 90-100
• K. Wong, C. Tam, G. Young, M. Ng and S. Wong, Improved Residue Function and Reduced Flow Dependence in MR Perfusion Using Least-absolute-deviation Regularization, Magnetic Resonance in Medicine, V61 (2009), pp. 418-428
• Y. Huang, M. Ng and Y. Wen, A New Total Variation Method for Multiplicative Noise Removal, SIAM Journal on Imaging Sciences, V2 (2009), pp. 20-40
• L. Lu, M. Ng, F. Lin, Approximation BFGS Methods for Nonlinear Image Restoration, Journal of Computational and Applied Mathematics, 226 (2009), 84-91
• Y. Wen, M. Ng and Y. Huang, Efficient Total Variation Minimization Methods for Color Image Restoration, IEEE Transactions on Image Processing, V17 (2008), pp. 2081-2088
• Y. Huang, M. Ng and Y. Wen, A Fast Total Variation Minimization Method for Image Restoration, SIAM Journal on Multiscale Modeling and Simulation, V7 (2008), pp. 774-795
• Y. Wen, N. Ng and W. Ching, Iterative Algorithms Based on Decoupling of Deblurring and Denoising for Image Restoration, SIAM Journal on Scientific Computing, V30 (2008), pp. 2655-2674
• M. Nikolova, M. Ng, S.Zhang and W. Ching, Efficient Reconstruction of Piecewise Constant Images Using Nonsmooth Nonconvex Minimization, SIAM Journal on Imaging Sciences, V1 (2008), pp. 2-25
• Y. Huang and M. Ng, Lipschitz and Total-Variational Regularization for Blind Deconvolution, Communications in Computational Physics, V4 (2008), pp. 195-206
• M. Ng, H. Shen, S. Chaudhuri, A. Yau, A Zoom Based Super-Resolution Reconstruction Approach Using Total Variation Prior, Optical Engineering, V46 (2007), 127003
• M. Ng, H. Shen, L. Zhang and E. Lam, A Total Variation Regularization Based Super-Resolution Reconstruction Algorithm for Digital Video, EUASIP Journal on Advances in Signal Processing, V2007 (2007), Article ID 74585, 16 pages
• M. Ng, L. Qi, Y. Yang and Y. Huang, On Semismooth Newton's Methods for Total Variation Minimization, Journal of Mathematical Imaging and Vision, V27 (2007), pp. 265-276
• T. Chan, N. Ng, A. Yau and A. Yip, Superresolution Image Reconstruction Using Fast Inpainting Algorithms, Applied and Computational Harmonic Analysis, V23 (2007), pp. 3-24
• H. Fu, M. Ng and J. Barlow, Structured Total Least Squares for Color Image Restoration, SIAM Journal on Scientific Computing, V28 (2007), pp. 1100-1119
• W. Chan, E. Lam, M. Ng and G. Mak, Super-resolution Reconstruction in a Computational Compound-eye Imaging System, Multidimensional Systems and Signal Processing, V18 (2007), pp. 83-101
• A. Yau, N. Bose and M. Ng, An Efficient Algorithm for Superresolution in Medium Field Imaging, Multidimensional Systems and Signal Processing, V18 (2007), pp. 173-188
• J. Zhang, T. Zhou, C. Cheung, C. Beling, S. Fung, M. Ng, Deconvolution of 2D coincident Doppler broadening spectroscopy using the Richardson-Lucy algorithm, Nuclear Instruments and Methods in Physics Research A, V560 (2006), pp. 552-557
• N. Bose, M. Ng and A. Yau, A Fast Algorithm for Image Super-Resolution From Blurred Observations, EURASIP Journal on Applied Signal Processing, V2006 (2006), Article ID 35726, 14 pages
• H. Fu, M. Ng, M. Nikolova and J. Barlow, Efficient Minimization Methods of Mixed L1-L1 and L2-L1 Norms for Image Restoration, SIAM Journal on Scientific Computing, V27 (2006), pp. 1881-1902
• M. Nikolova and M. Ng, Analysis of Half-Quadratic Minimization Methods for Signal and Image Recovery, SIAM Journal on Scientific Computing, V27 (2006), pp. 937-966
• M. Ng and A. Yau, Super-resolution Image Restoration from Blurred Low-resolution Images, Journal of Mathematical Imaging and Vision, V23 (2005), pp. 367-378
• T. Woo, V. Cheng, C. Beling and M. Ng, An Evaluation of Algorithms for the Deconvolution of Doppler Broadening Positron Annihilation Radiation Spectroscopy Spectra, Computer Physics Communications, V168, Issue 3 (2005), pp. 177-186
• H. Ngan, G. Pang, S. Yung and M. Ng, Wavelet Based Methods for Patterned Fabric Defect Detection, Pattern Recognition, V38 (2005), pp. 559-576
• W. Ching, M. Ng, K. Sze and A. Yau, Super-Resolution Image Reconstruction Using Multisensors, Numerical Linear Algebra with Applications, V12 (2005), pp. 271-281
• M. Ng and W. Kwan, Image Restoration by Cosine Transform Based Iterative Regularization, Applied Mathematics and Computation, V160 (2005), pp. 499-515
• R. Peeters, P. Kornprobst, M. Nikolova, S. Sunaert, T. Vieville, G. Malandain, R. Deriche, O. Faugeras, M. Ng and P. Van Hecke, The Use of Superresolution Techniques to Reduce Slice Thickness in Functional MRI, International Journal of Imaging System and Technology, V14 (2004), pp. 131-138
• F. Lin, W. Ching and M. Ng, Preconditioning Regularized Least Squares Problems Arising from High-Resolution Image Reconstruction from Low-Resolution Frames, Linear Algebra and its Applications, V391 (2004), pp. 149-168
• M. Ng, S. Sze and S. Yung, Wavelet Algorithms for Deblurring Models, International Journal of Imaging System and Technology, V14(3) (2004), pp. 113-121
• Y. Wen, M. Ng and W. Ching, High-Resolution Image Reconstruction from Rotated and Translated Low-Resolution Images with Multisensors, International Journal of Imaging System and Technology, V14(2) (2004), pp. 75-83
• J. Nagy, M. Ng and L. Perrone, Kronecker Product Approximation for Image Restoration with Reflexive Boundary Conditions, SIAM Journal Matrix Analysis and Applications, V25 (2004), pp. 842-857
• W. Ching, M. Ng, K. Sze and A. Yau, Super-Resolution Image Restoration from Blurred Observations by Multisensors, International Journal of Imaging Systems and Technology, V13 (2003), pp. 153-160
• F. Lin and M. Ng, Super-Resolution Image Reconstruction with Estimation of Low-Resolution Frames, International Journal of Applied Mathematics, V13 (2003), pp. 84-99
• F. Ho, A. Ching, C. Beling, S. Fung, M. Ng, M. Biasini, G. Ferro, M. Gong, Positron-electron Autocorrelation Function Study of E-center in Silicon, Journal of Applied Physics, V94 (2003), pp. 5549-5555
• M. Ng and N. Bose, Mathematical Analysis of Super-Resolution Methodology, IEEE Signal Processing Magazine, V20 (2003), pp. 62-74
• K. Ho, C. Beling, S. Fung, K. Cheng, M. Ng and A. Yip, Deconvolution of Coincidence Doppler Broadening Spectra using Iterative Projected Newton Method with Non-negativity Constraints, Review of Scientific Instruments, V74 (2003), pp. 4779-4787
• M. Ng and N. Bose, Fast Color Image Restoration with Multisensors, International Journal of Imaging Systems and Technology, V12 (2003), pp. 189-197
• M. Ng and N. Bose, Analysis of Displacement Errors in High-Resolution Image Reconstruction with Multisensors, IEEE Transactions on Circuits and Systems: Part I, V49 (2002), pp. 806-813
• M. Ng, A Fast Algorithm for Blind Channel Identification, The Journal of Mathematical and Physical Sciences, V1 (2002), pp. 92-103
• M. Ng, J. Koo and N. Bose, Constrained Total Least Squares Computations for High Resolution Image Reconstruction with Multisensors, International Journal of Imaging Systems and Technology, V12 (2002), pp. 35-42
• M. Ng and W. Kwan, Comments on Least Squares Restoration of Multichannel Images, IEEE Transactions on Signal Processing, V49 (2001), p. 2885
• M. Ng and W. Kwan, High-Resolution Color Image Reconstruction with Neumann Boundary Conditions, Annals of Operations Research, V103 (2001), pp. 99-114
• M. Ng and A. Yip, A Fast MAP Algorithm for High-Resolution Image Reconstruction with Multisensors, Multidimensional Systems and Signal Processing, V12 (2001), pp. 143-164
• M. Ng, Robert Plemmons and Felipe Pimentel, A New Approach to Constrained Total Least Squares Image Restoration, Linear Algebra Appls., V316 (2000), pp. 237-258
• M. Ng, R. Chan, T. Chan and A. Yip, Cosine Transform Preconditioners for High Resolution Image Reconstruction, Linear Algebra Appls., V316 (2000), pp. 89-104
• M. Ng, R. Chan and W. Tang, A Fast Algorithm for Deblurring Models with Neumann Boundary Conditions, SIAM Journal on Scientific Computing, V21 (2000), pp. 851-866
• M. Ng, R. Plemmons and S. Qiao, Regularization of RIF Blind Image Deconvolution, IEEE Transactions on Image Processing, V9 (2000), pp. 1130-1134
• M. Ng, FFT--based Exponential-weighted Least Squares Computations, Linear Algebra and its Applications, V263 (1997), pp. 167-191
• M. Ng and R. Plemmons, LMS-Newton Adaptive Filtering Using FFT, SEAMS Math. Bulletin, V20 (1996), pp. 47-54
• M. Ng and R. Plemmons, Fast RLS Adaptive Filtering by FFT--based Conjugate Gradient Iterations, SIAM Journal on Scientific Computing, V17 (1996), pp. 920-941
• M. Ng and R. Plemmons, LMS-Newton Adaptive Filtering Using FFT--based Conjugate Gradient Iterations, Electronic Transactions on Numerical Analysis, V4 (1996), pp. 14-36
• R. Chan, M. Ng and R. Plemmons, Generalization of Strang's Preconditioner with Applications to Toeplitz Least Squares Problems, Numerical Linear Algebra with Applications, V3 (1996), pp. 45-64
• M. Ng, Fast Iterative Method for Solving Toeplitz-plus-Hankel Least Squares Problems, Electronic Transactions on Numerical Analysis, V2 (1994), pp. 154-170
• M. Ng and R. Chan, Fast Iterative Method for Least Squares Estimations, Numerical Algorithms, V6 (1994), pp. 353-378

• X. Lin, X. Lu, M. Ng, H. Sun, A Fast Accurate Approximation Method with Multigrid Solver for Two-Dimensional Fractional Sub-Diffusion Equation, Journal of Computational Physics, V323 (2016), pp. 204-218
• R. Ke, M. Ng and H. Sun, A Fast Direct Method for Block Triangular Toeplitz-like with Tri-diagonal Block Systems from Time-Fractional Partial Differential Equations, Journal of Computational Physics, V303 (2015), pp. 203-211
• M. Benzi, M. Ng, Q. Niu and Z. Wang, A Relaxed Dimensional Factorization Preconditioner for the Incompressible Navier-Stokes Equations, Journal of Computational Physics, V230 (2011), pp. 6185-6202
• Z. Bai, Y. Huang and M. Ng, On Preconditioned Iterative Methods for Time-dependent Partial Differential Equations, SIAM Journal on Numerical Analysis, V47 (2009), pp. 1019-1037
• Z. Bai, Y. Huang and M. Ng, On Preconditioned Iterative Methods for Burgers Equations, SIAM Journal on Scientific Computing, V29 (2007), pp. 415-439
• Z. Bai, M. Ng and J. Pan, On Alternating Splitting Waveform Relaxation Method and its Successive Overrelaxation Acceleration, Computers and Mathematics with Applications, V49 (2005), pp. 157-170
• J. Pan, Z. Bai and M. Ng, Two-Step Waveform Relaxation Methods for Implicit Linear Initial Value Problems, Numerical Linear Algebra with Applications, V12 (2005), pp. 293-304
• D. Bertaccini, Y. Wen and M. Ng, The Eigenvalues of Preconditioned Matrices for Linear Multistep Formulas in Boundary Value Form, Numerical Linear Algebra with Applications, V12 (2005), pp. 315-325
• D. Bertaccini and M. Ng, Band-Toeplitz Preconditioned GMRES Iterations for Time-dependent PDEs, BIT, V43 (2003), pp. 901-914
• D. Bertaccini and M. Ng, Omega-Circulant Preconditioners for Time-Dependent Integrators, CALCOLO, V40 (2003), pp. 71-90
• W. Cheung and M. Ng, Block-Circulant Preconditioners for Systems Arising from Discretization of the Three-Dimensional Convection-Diffusion Equation, Journal of Computational Applied Math., V140 (2002), pp. 143-158
• R. Chan, M. Ng and X. Jin, Strang's Circulant Preconditioners for Systems of LMF-Based ODE Codes, IMA Journal of Numerical Analysis, V21 (2001), pp. 451-462
• D. Bertaccini and M. Ng, The Convergence Rate of Block Preconditioned Systems Arising from LMF-based ODE Codes, BIT, V41 (2001), pp. 433-450
• F. Lin and M. Ng, Fast Preconditioned Iterative Methods for Convolution-type Integral Equations, BIT, V40 (2000), pp. 336-350
• M. Ng, Preconditioning of Elliptic Problems by Approximation in the Transform Domain, BIT, V37 (1997), pp. 885-900
• F. Lin, M. Ng and R. Chan, Preconditioners for Wiener-Hopf Equations with Higher Order Quadrature Rules, SIAM Journal on Numerical Analysis, V34 (1997), pp. 1418-1431
• M. Ng, Circulant Preconditioners for Convolution-like Integral Equations with Higher Order Quadrature Rules, Electronic Transactions on Numerical Analysis, V5 (1997), pp. 18-28
• M. Ng and F. Lin, Decomposition and Construction of Preconditioners for Wiener-Hopf Equations, SEAMS Math. Bulletin, V20, No. 3 (1996), pp. 71-78
• F. Lin and M. Ng, Higher-order Quadratures for Circulant Preconditioned Wiener-Hopf Equations, BIT, V36, No.1 (1996), pp. 110-121
• R. Chan, X. Jin and M. Ng, Circulant Integral operators as Preconditioners for Wiener-Hopf Equations, Integral Equations and Operator Theory, V21 (1995), pp. 12-23
• M. Ng, F. Lin and R. Chan, Construction of Preconditioners for Wiener-Hopf Equations by Operator Splitting, Applied Mathematics and Computations, V72 (1995), pp. 77-96

• G. Gan and M. Ng, k-Means Clustering with Outlier Removal, Pattern Recognition Letters, V90 (2017), pp. 8-14
• M. Ng, Q. Wu and C. Shen, A Fast Markov Chain Based Algorithm for MIML Learning, Neurocomputing, V216 (2016), pp. 763-777
• Q. Wu, M. Tan, M. Song, H. Chen and M. Ng, ML-Forest: A Multi-label Tree Ensemble Method for Multi-Label Classification, IEEE Transactions on Knowledge and Data Engineering, V28 (2016), pp. 2665-2680
• X. Li, M. Ng, G. Cong, Y. Ye and Q. Wu, MR-NTD: Manifold Regularization Nonnegative Tucker Decomposition for Tensor Data Dimension Reduction and Representation, IEEE Transactions on Neural Networks and Learning Systems,
• L. Yang, L. Jing, J. Yu and M. Ng, Learning Transferred Weights from Co-Occurrence Data for Heterogeneous Transfer Learning, IEEE Transactions on Neural Networks and Learning Systems, V27 (2016), pp. 2187-2200
• G. Gan and M. Ng, Subspace Clustering with Automatic Feature Grouping, Pattern Recognition, V48 (2015), pp. 3703-3713
• D. Chu, L. Liao, M. Ng and X. Wang, Incremental Linear Discriminant Analysis: A New Algorithm and Comparisons, IEEE Transactions on Neural Networks and Learning Systems, V11 (2015), pp. 2716-2735
• G. Gan and M. Ng, Subspace Clustering using Affinity Propagation, Pattern Recognition, V48 (2015), pp. 1455-1464
• Q. Wu, Y. Ye, H. Zhang, M. Ng and S. Ho, ForesTexter: An Efficient Random Forest Algorithm for Imbalanced Text Categorization, Knowledge-Based Systems, V67 (2014), pp. 105-116
• Q. Wu, M. Ng, Y. Ye, X. Li, R. Shi and Y. Li, Multi-Label Collective Classification via Markov Chain Based Learning Method, Knowledge Based System V63 (2014), pp. 1-14
• Q. Wu, M. Ng and Y. Ye, Co-Transfer Learning Using Coupled Markov Chains with Restart, IEEE Intelligent Systems, V29 (2014), pp. 26-33
• D. Chu, L. Liao, M. Ng and X. Zhang, Sparse Canonical Correlation Analysis: New Formulation and Algorithm, IEEE Transactions on Pattern Analysis and Machine Intelligence, V35 (2013), pp. 3050-3065
• L. Jing, M. Ng, T. Zeng, Dictionary Learning Based Subspace Structure Identification in Spectral Clustering, IEEE Transactions on Neural Networks and Learning Systems, V24 (2013), pp. 1188-1199
• X. Li, M. Ng, and Y. Ye, MultiComm: Finding Local Community Structure in Multi-dimensional Networks, IEEE Transactions on Knowledge and Data Engineering, V26 (2014), pp. 929-941
• Y. Ye, Q. Wu, J. Huang, M. Ng and X. Li, Stratified Sampling for Feature Subspace Selection in Random Forests for High Dimensional Data, Pattern Recognition, V46 (2013), pp. 769-787
• Q. Wu, M. Ng and Y. Ye, Markov-MIML: A Markov Chain Based Multi-Instance Multi-Label Learning Algorithm, Knowledge and Information Systems, V37 (2013), pp. 83-104
• X. Kong, M. Ng and Z. Zhou, Transductive Multi-Label Learning via Label Set Propagation, IEEE Transactions on Knowledge and Data Engineering, V25 (2013), pp. 704-719.
• X. Li, W. Li, Y. Ye and M. Ng, On Multivariate Markov Chains for Common and Non-common Objects in Multiple Networks, Numerical Mathematics: Theory, Methods and Applications, V5 (2012), pp. 383-402
• Y. Wang, Y. Ye, X. Li, M. Ng and J. Huang, Hierarchical Information-theoretic Co-clustering for High Dimensional Data, International Journal of Innovative Computing, Information and Control, V7 (2011), pp. 487-500
• M. Ng, L. Liao and L. Zhang, On Sparse Linear Discriminant Analysis Algorithm for High-dimensional Data Classification, Numerical Linear Algebra with Applications, V18 (2011), pp. 223-236
• X. Li, Y. Ye, M. Li and M. Ng, On Cluster Tree for Nested and Multi-density Data Clustering, Pattern Recognition, V43 (2010), pp. 3130-3143
• J. Ling, M. Ng and J. Huang, Knowledge-based Vector Space Model for Text Clustering, Knowledge and Information Systems, V25 (2010), pp. 35-55
• J. Ling, M. Li, M. Ng, Y. Cheung and J. Huang, SMART: a Subspace Clustering Algorithm that Automatically Identifies the Appropriate Number of Clusters, International Journal of Data Mining, Modelling and Management, V1 (2009), pp. 149-177
• H. Liao and M. Ng, Categorical Data Clustering with Automatic Selection of Cluster Number, Journal of Fuzzy Information and Engineering, V1 (2009), pp. 5-25
• M. Ng and L. Jing, A New Fuzzy k-Modes Clustering Algorithm for Categorical Data, International Journal of Granular Computing, Rough Sets and Intelligent Systems, V1 (2009), pp. 105-119
• M. Li, M. Ng, Y. Cheung and J. Huang, Agglomerative Fuzzy k-means Algorithm with Selection of Number of Clusters, IEEE Transactions on Knowledge and Data Engineering, V20 (2008), pp. 1519-1534
• X. Zhang, L. Jing, X. Hu, M. Ng, J. Xia and X. Zhou, Medical Document Clustering Using Ontology Based Term Similarity Measures, International Journal of Data Warehousing and Mining, V4 (2008), pp. 62--73
• L. Jing, M. Ng and J. Huang, An Entropy Weighting k-means Algorithm for Subspace Clustering of High-dimensional Sparse Data, IEEE Transactions on Knowledge and Data Engineering, V19 (2007), pp. 1026-1041
• M. Ng, M. Li, J. Huang and Z. He, On the Impact of Dissimilarity Measure in k-modes Clustering Algorithm, IEEE Transactions on Pattern Analysis and Machine Intelligence, V29 (2007), pp. 503-507
• M. Ng, E. Chan, M. So and W. Ching, A Semi-Supervised Regression Model for Mixed Numerical and Categorical Variables, Pattern Recognition, V40 (2007), pp. 1745-1752.
• L. Jing, X. Yang, M. Ng, J. Huang, A Text Clustering System based on k-means Type Subspace Clustering and Ontology, International Journal of Intelligent Technology, Vol. 1, No. 2, pp. 91-103.
• V. Torra, J. Domingo-Ferrer, J. Mateo-Sanz and M. Ng, Regression for Ordinal Variables without Underlying Continuous Variables, Information Sciences, V176 (2006), pp. 465-474
• E. Wu, M. Ng and J. Huang, A Data Warehousing and Data Mining Framework for Web Usage Management, Communications in Information and Systems, V4 (2004), pp. 301-324.
• Z. Huang, M. Ng, H. Rong and Z. Li, Automated Variable Weighting in K-Means Type Clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence, V27 (2005), pp. 657-668
• K. Yip, D. Cheung and M. Ng, HARP: A Highly-usable Projected Clustering Algorithm, IEEE Transactions on Knowledge and Data Engineering, V16 (2004), pp. 1387-1397
• E. Chan, W. Ching, M. Ng and Z. Huang, An Optimization Algorithm for Clustering Using Weighted Dissimilarity Measures Optimization, Pattern Recognition, V37 (2004), pp. 943-952
• Z. Huang and M. Ng, A Note on K-Modes Clustering, Journal of Classification, V20 (2003), pp. 257-261
• Q. Yang, Z. Huang and M. Ng, A Data Cube Model for Prediction-based Web Prefetching, Journal of Intelligent Information Systems, V20 (2003), pp. 11-30
• K. Yip, M. Ng and D. Cheung, A Review on Projected Clustering Algorithms, International Journal of Applied Mathematics, V13 (2003), pp. 24-35
• M. Ng and J. Wong, Clustering Categorical Data Sets Using Tabu Search Techniques, Pattern Recognition, V35 (2002), pp. 2783-2790
• M. Ng, K-means-type Algorithms on Distributed Memory Computer, International Journal of High Speed Computing, V11 (2001), pp. 75-91
• M. Ng, A Note on Constrained K-means Algorithms, Pattern Recognition, V33 (2000), pp. 515-519
• Z. Huang and M. Ng, A Fuzzy K-modes Algorithm for Clustering Categorical Data, IEEE Transactions on Fuzzy Systems, V7 (1999), pp. 446-452
• M. Ng and Z. Huang, Data-Mining Massive Time Series Astronomical Data: Challenges, Problems and Solutions, Information and Software Technology, V41 (1999), pp. 545-556

• C. Chuan, M. Ng and S. Zhang, Block Spectral Clustering for Multiple Graphs with Inter-relation, Network Modeling Analysis in Health Informatics (2017)
• X. Zhang, L. Li, M. Ng and S. Zhang, Drug-target Interaction Prediction by Integrating Multiview Network Data, Computational Biology and Chemistry (2017)
• S. Zhang and M. Ng, Gene-microRNA Network Module Analysis for Ovarian Cancer, BMC System Biology, Volume 10 Supplement 4 (2016)
• C. Shen, J. Pan, S. Zhang and M. Ng, Multiple Networks Modules Identification by a Multi-dimensional Markov Chain Method, Network Modeling Analysis in Health Informatics and Bioinformatics, 4:32 (2015)
• S. Zhang, H. Zhao and M. Ng, Functional Module Analysis for Gene Coexpression Networks with Network Integration, IEEE/ACM Transactions on Computational Biology and Bioinformatics, V12 (2015), pp. 1146-1160
• H. Cai, P. Ruan, M. Ng and T. Akutsu, Feature Weight Estimation for Gene Selection: a Local Hyper-Linear Learning Spproach, BMC Bioinformatics, 15:70 (2014)
• Q. Wu, Y. Ye, M. Ng, S. Ho and R. Shi, Collective Prediction of Protein Functions from Protein-Protein Interaction Networks, BMC Bioinformatics, 15:S9 (2014)
• X. Li, Y. Ye, M. Ng and Q. Wu, MultiFacTV: Module Detection from Higher-order Time Series Biological Data, BMC Genomics 14:S2 (2013)
• H. Pang, T. Tong and M. Ng, Block-diagonal Discriminant Analysis and Its Bias-corrected Rules, Statistical Applications in Genetics and Molecular Biology, V12 (2013), pp. 347-359
• Y. Liu, X. Li, Z. Liu, L. Chen and M. Ng, Construction and Analysis of SNP-SNP Interaction Networks, IET Systems Biology, V7 (2013), pp. 170-181
• Q. Wu, Y. Ye, Y. Liu and M. Ng, Stratified Random Forest for Genome-wide Association Study, IEEE Transactions on NanoBioScience, V11 (2012), pp. 216-227
• Y. Liu and M. Ng, Classification of Genome-wide Copy Number Variations and their Associated SNP and Gene Networks Analysis, BMC Bioinformatics, 12:S4 (2011)
• L. Jing, T. Zeng and M. Ng, On Gene Selection and Classification for Cancer Microarray Data Using Multi-step Clustering and Sparse Representation, Advances in Adaptive Data Analysis, V3 (2011), pp. 127-148
• L. Jing and M. Ng, Prior Knowledge Based Mining Functional Modules from Yeast PPI Networks with Gene Ontology, BMC Bioinformatics, 11:S3 (2010)
• Y. Liu and M. Ng, Shrunken Methodology to Genome-wide SNPs Selection and Construction of SNPs Networks, BMC Systems Biology, 4:S7, (2010)
• Y. Liu, M. Li, Y. Cheung, P. Sham and M. Ng, SKM-SNP: SNP Markers Detection Method, Journal of Biomedical Informatics, V43 (2010), pp. 233-239
• L. Jing, M. Ng and Y. Liu, Construction of Gene Networks with Hybrid Approach from Expression Profile and Gene Ontology, IEEE Transactions on Information Technology in Biomedicine, V14 (2010), pp. 107-118
• S. Zhang, H. Wang, X. Zhou, G. Hoehn, T. DeGraba, D. Gonzales, A. Suffredini, W. Ching, M. Ng and S. Wong, A Novel Peak Detection Approach with Chemical Noise Removal Using Short-Time FFT for prOTOF MS Data, Proteomics, V9 (2009), pp. 3833-3842
• X. Hu, M. Ng, F. Wu and B. Sokhansanj, Mining, Modeling and Evaluation of Sub-Networks from Large Biomolecular Networks and its Comparison Study, IEEE Transactions on Information Technology in Biomedicine, V13 (2009), pp. 184-194
• T. Akutsu, M. Hayashida, S. Zhang, W. Ching and M. Ng, Analyses and Algorithms for Predecessor and Control Problems for Boolean Networks of Bounded Indegree, IPSJ Transactions on Bioinformatics, V1 (2008), pp. 23-34
• K. Yip, L. Cheung, D. Cheung, L. Jing and M. Ng, A Semi-supervised Approach to Projected Clustering with Applications to Microarray Data, International Journal of Data Mining and Bioinformatics, V3 (2009), pp. 229-259
• E. Fung and M. Ng, On Sparse Fisher Discriminant Method for Microarray Data Analysis, Bioinformation, V2 (2007), pp. 222-229
• H. Liao, M. Ng, E. Fung and P. Sham, Unidimensional Nonnegative Scaling for Genome-wide Linkage Disequilibrium Maps, International Journal of Bioinformatics Research and Applications, V4 (2008), pp. 417-434
• L. Cheung, Y. Lee, T. Ng, W. Ching, U. Khoo, M. Ng and A. Wong, CpG/CpNpG Motifs in the Coding Region are Preferred Sites for Mutagenesis in the Breast Cancer Susceptibility Genes, FEBS Letters, V581 (2007), pp. 4668-4674
• W. Ching, S. Zhang, M. Ng and T. Akutsu, An Approximation Method for Solving the Steady-state Probability Distribution of Probabilistic Boolean Networks, Bioinformatics, V23 (2007), pp. 1511-1518
• S. Zhang, M. Hayashida, T. Akutsu, W. Ching and M. Ng, Algorithms for Finding Small Attractors in Boolean Networks, EURASIP Journal on Bioinformatics and Systems Biology, V2007 (2007), 20180
• P. Sham, S. Ao, P. Koo, P. Yee and M. Ng, Combining Functional and Linkage Disequilibrium Information in the Selection of Tag SNPs, Bioinformatics V23 (2007), pp. 129-131
• T. Akutsu, M. Hayashida, W. Ching and M. Ng, Control of Boolean Networks: Hardness Results and Algorithms for Tree Structured Networks, Journal of Theoretical Biology, V244 (2007), pp. 670-679
• A. Yip, M. Ng, E. Wu and T. Chan, Strategies for Identifying Statistically Significant Dense Regions in Microarray Data, IEEE/ACM Transactions on Computational Biology and Bioinformatics, V4(3) (2007), pp. 415-429
• S. Ao, M. Ng and P. Sham, Constrained Unidimensional Scaling with Applications to Genomics, Computational Statistics and Data Analysis, V52 (2007), pp. 201-210
• S. Zhang, W. Ching, M. Ng and T. Akutsu, Simulation Study in Probabilistic Boolean Network Models for Genetic Regulatory Networks, International Journal of Data Mining and Bioinformatics, V1 (2007), pp. 217-240
• M. Ng, E. Fung, Y. Li and W. Ching, A Recursive Method for Solving Haplotype Frequencies with Application to Genetics, Journal of Bioinformatics and Computational Biology, V4 (2007) pp. 1269-1286
• C. Lin, K. Yip, D. Cheung, B. Kao and M. Ng, On Mining Micro-array Data by OPSM, International Journal of Bioinformatics Research and Applications, V3 (2007), pp. 42-64.
• S. Ao and M. Ng, Gene Expression Time Series Modeling with Principal Component and Neural Network, Soft Computing, V10 (2006), pp. 351-358
• W. Ching, M. Ng, E. Fung and T. Akutsu, On Construction of Stochastic Genetic Networks Based on Gene Expression Sequences, International Journal of Neural Systems, 15 (2005) pp. 297-310
• S. Ao, K. Yip, M. Ng, D. Cheung, P. Yee, I. Melhado and P. Sham, CLUSTAG: Hierarchical Clustering and Graph Methods for Selecting Tag SNPs, Bioinformatics, V21 (2005) pp. 1735-1736
• K. Yip, D. Cheung, M. Ng and K. Cheung, Identifying Projected Clusters from Gene Expression Profiles, Journal of Biomedical Informatics, V37 (2004) pp. 345-357

• M. Ng and Y. Chung, Double Mover-stayer Model on Customer Switching in Telecommunication Industry, Naval Research Logistics, V59 (2012) pp. 663-674
• G. Fusai, D. Marazzina, M. Marena and M. Ng, Z-transform and Preconditioning Techniques for Option Pricing, Quantitative Finance, V12 (2012), pp. 1381-1394
• T. Siu, E. Fung and M. Ng, Option Valuation with a Discrete-Time Double Markovian Regime-Switching Model, Applied Mathematical Finance, V18 (2011), pp. 473-490
• T. Siu, W. Ching, E. Fung, M. Ng and X. Li, A Higher-order Markov-switching Model for Risk Measurement, Computers and Mathematics Applications, 58 (2009), pp. 1-10
• W. Ching, E. Fung, M. Ng, T. Siu and W. Li, Interactive Hidden Markov Models and Their Applications, IMA Journal of Management Mathematics, V18 (2007), 85-97
• K. Siu, M. Ng and E. Fung, On Neural Network Conditional Autoregressive Value at Risk, Mathematical Modelling and Applied Computing
• W. Ching, S. Zhang and M. Ng, On Multi-dimensional Markov Chain Models, Pacific Journal of Optimization, V3 (2007), 235-243
• T. Siu, W. Ching. E. Fung and M. Ng, Extracting Information from Spot Interest Rates and Credit Ratings using Double Higher-Order Hidden Markov Models, Journal of Computational Economics 26 (2005) 251-284
• W. Ching, W. Yuen, M. Ng, and S. Zhang A Linear Programming Approach for Determining Optimal Advertising Policy, IMA Journal of Management Mathematics, V17 (2006) pp. 83-96
• T. Siu, W. Ching, E. Fung and M. Ng, On Multivariate Credibility Approach for Portfolio Credit Risk Measurement, Quantitative Finance, V5 (2005), pp. 543-556
• W. Ching, E. Fung and M. Ng, Building Higher-order Markov Chain Models with EXCEL, International Journal of Mathematical Education in Science and Engineering, V35 (2004), pp. 921-932
• W. Ching, M. Ng, K. Wong and E. Altman, Customer Lifetime Value: Stochastic Optimization Approach, Journal of Operational Research Society, V55 (2004), pp. 860-868
• W. Ching, M. Ng and M. So, Customer Migration, Campaign Budgeting, Revenue Estimation: the Elasity of Markov Decision Process on Customer Lifetime Value, Electronic International Journal of Advanced Modeling and Optimization, V6(2) (2004), pp. 65-80
• W. Ching, M. Ng, and K. Wong, Hidden Markov Models and its Applications to Customer Relationship Management, IMA Journal on Management Mathematics, V15 (2004), pp. 13-24
• W. Ching and M. Ng, Building Simple Hidden Markov Model, International Journal of Mathematical Education in Science and Technology, V35 (2004), pp. 295-299
• W. Ching, E. Fung and M. Ng, Higher-order Markov Chain Models for Categorical Data Sequences, Naval Research Logistics, V51 (2004), pp. 557-574
• W. Ching, E. Fung and M. Ng, Higher-order Markov Model for the Newsboy's Problem, Journal of Operational Research Society, V54 (2003), pp. 291-298
• W. Ching, E. Fung and M. Ng, A Multivariate Markov Chain Model for Categorical Data Sequences and Its Applications in Demand Predictions, IMA Journal on Management Mathematics, V13 (2002) 187-199
• M. Ng, Clustering Methods for Printed Circuit Board Insertion Problems, Journal of Operational Research Society, V51 (2000), pp. 1205-1211
• M. Ng, A Note on Policy Algorithms for Discounted Markov Decision Problems, Operations Research Letters, V25 (1999), pp. 195-197
• M. Ng, Heuristics Approach to Printed Circuit Board Insertion Problem, Journal of Operational Research Society, V49 (1998), pp. 1051-1059

• Y. Sun, M. Ng, Z. Zhou: Multi-Instance Dimensionality Reduction. AAAI 2010

• R. Chan and M. Ng, Preconditioning Toeplitz Systems with Circulant Preconditioners, Iterative Methods in Scientific Computing, Springer-Verlag, 1997, pp. 243-270
• R. Chan and M. Ng, Iterative Methods for Linear Systems with Matrix Structure, Fast Reliable Algorithms for Matrices with Structure, SIAM, 1999, pp. 132-174
• R. Chan, M. Ng and X. Jin, Circulant Preconditioners for Solving Ordinary Differential Equations, Structured Matrices: Recent Developments in Theory and Computation. Nova Science Pub. Inc., 2000, pp. 157-164
• W. Kwan and M. Ng, Iterative Regularization for Ill-Posed Imaging Problems Using Neumann Boundary Conditions, Structured Matrices: Recent Developments in Theory and Computation, Nova Science Pub. Inc., 2000, pp. 177-190
• R. Chan, M. Ng and A. Yip, A Survey of Preconditioners for Ill-Conditioned Toeplitz Systems, Structured Matrices in Mathematics, Computer Science, and Engineering II, Contemporary Mathematics, AMS, 2001, pp. 175-191
• M. Ng, N. Bose and J. Koo, Constrained Total Least Squares for Color Image Reconstruction, Total Least Squares and Errors-in-Variables Modelling III: Analysis, Algorithms and Applications, Kluer Academic Publishers, 2002, pp. 365-374
• M. Ng and R. Plemmons, Blind Deconvolution and Structured Matrix Computations with Applications to Array Imaging, Blind Image Deconvolution: Theory and Applications, CRC Press, pp. 377-418
• M. Ng, Structured Matrix Computations, Handbook of Linear Algebra, CRC Press, CRC Press, Chapter 48
• E. Wu and M. Ng, Developing a Knowledge-Based Intelligent Services System in Sports Websites, E-Service Intelligence---Methodologies, Technologies and Applications, Springer, Chapter 25, pp. 535-554