M
Michael K. Ng
Researcher at University of Hong Kong
Publications - 658
Citations - 24376
Michael K. Ng is an academic researcher from University of Hong Kong. The author has contributed to research in topics: Cluster analysis & Computer science. The author has an hindex of 72, co-authored 608 publications receiving 20492 citations. Previous affiliations of Michael K. Ng include The Chinese University of Hong Kong & Vanderbilt University.
Papers
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Journal ArticleDOI
Fast iterative methods for symmetric sinc-Galerkin systems
TL;DR: It is shown that the solution of an n-by-n discrete symmetric sinc-Galerkin system can be obtained in O(n log n) operations and it is proved that the condition number of the preconditioned matrix is uniformly bounded by a constant independent of the size of the matrix.
Posted Content
3D Point Cloud Denoising using Graph Laplacian Regularization of a Low Dimensional Manifold Model
TL;DR: In this article, a patch-based graph Laplacian regularizer was proposed to quantify the similarity between two same-sized surface patches for graph construction that is robust to noise.
Journal ArticleDOI
Functional Module Analysis for Gene Coexpression Networks with Network Integration
TL;DR: An effective method for module identification from multiple networks under different conditions is developed and the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.
Journal ArticleDOI
Medical Document Clustering Using Ontology-Based Term Similarity Measures
TL;DR: A comparative study on how different term semantic similarity measures including path-based, information-content-based and feature-based similarity measure affect document clustering and finds no certain type of similarity measures that significantly outperforms the others.
Book ChapterDOI
A control model for markovian genetic regulatory networks
TL;DR: The main objective of this paper is to approximate the above control problem and formulate as a minimization problem with integer variables and continuous variables using dynamics of states probability distribution of genes.