Wai-Ki Ching spends much of his time researching Markov chain, Mathematical optimization, Algorithm, Markov model and Queueing theory. His Markov chain study frequently intersects with other fields, such as Markov process. His Mathematical optimization research includes themes of Closed loop, Communication channel, Dual and Operations management.
His Boolean network and Regularization study in the realm of Algorithm connects with subjects such as Vertex and Singleton. As a member of one scientific family, Wai-Ki Ching mostly works in the field of Markov model, focusing on Artificial intelligence and, on occasion, Optimization algorithm, Pattern recognition, Systems biology and Biological network. His research in Variable-order Markov model intersects with topics in Markov property and Hidden Markov model.
His primary scientific interests are in Mathematical optimization, Markov chain, Artificial intelligence, Econometrics and Algorithm. His Mathematical optimization study incorporates themes from Probability distribution and Probabilistic logic. His work is dedicated to discovering how Probabilistic logic, Theoretical computer science are connected with Attractor and other disciplines.
His Markov chain study deals with Markov process intersecting with Operations research. His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning, Data mining and Pattern recognition. His research in Algorithm is mostly concerned with Boolean network.
His primary areas of investigation include Markov chain, Mathematical optimization, Econometrics, Boolean network and Complex network. Wai-Ki Ching interconnects Volatility, Valuation of options and Hidden Markov model in the investigation of issues within Markov chain. Wai-Ki Ching performs integrative study on Mathematical optimization and Negotiation.
His Boolean network study integrates concerns from other disciplines, such as Upper and lower bounds, Topology, Aperiodic graph and Lyapunov function. His Complex network study also includes fields such as
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Control of Boolean networks: hardness results and algorithms for tree structured networks.
Tatsuya Akutsu;Morihiro Hayashida;Wai-Ki Ching;Michael K. Ng.
Journal of Theoretical Biology (2007)
Markov Chains: Models, Algorithms and Applications
Wai-Ki Ching;Ximin Huang;Michael K. Ng;Tak Kuen Siu.
Analysis for strategy of closed-loop supply chain with dual recycling channel
Min Huang;Min Song;Loo Hay Lee;Loo Hay Lee;Wai Ki Ching.
International Journal of Production Economics (2013)
An optimization algorithm for clustering using weighted dissimilarity measures
Elaine Y. Chan;Wai-Ki Ching;Michael K. Ng;Joshua Zhexue Huang.
Pattern Recognition (2004)
Markov Chains: Models, Algorithms and Applications (International Series in Operations Research & Management Science)
Wai-KI Ching;Michael K. Ng;W. Ching.
Efficient Reconstruction of Piecewise Constant Images Using Nonsmooth Nonconvex Minimization
Mila Nikolova;Michael K. Ng;Shuqin Zhang;Wai-Ki Ching.
Siam Journal on Imaging Sciences (2008)
Higher-order multivariate Markov chains and their applications
Wai-Ki Ching;Michael K. Ng;Eric S. Fung.
Linear Algebra and its Applications (2008)
On supply chain coordination for false failure returns: A quantity discount contract approach
Ximin Huang;Sin Man Choi;Wai Ki Ching;Tak Kuen Siu.
International Journal of Production Economics (2011)
Algorithms for finding small attractors in boolean networks
Shu-Qin Zhang;Morihiro Hayashida;Tatsuya Akutsu;Wai-Ki Ching.
Eurasip Journal on Bioinformatics and Systems Biology (2007)
Iterative Algorithms Based on Decoupling of Deblurring and Denoising for Image Restoration
You-Wei Wen;Michael K. Ng;Wai-Ki Ching.
SIAM Journal on Scientific Computing (2008)
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