Machine Learning

TC Leadership

Daniel S. Yeung

TC Chair

Daniel S. Yeung (Email)
South China University of Technology, China

Wing Yin Ng

TC Chair

Wing Yin Ng (Email)
South China University of Technology, China

Witold Pedrycz

TC Chair

Witold Pedrycz (Email)
University of Alberta, Canada


Our Goal

Machine Learning is the study of computer algorithms that improve automatically through experience. Applications range from data mining programs that discover general rules in large data sets, to information filtering systems that automatically learn users’ interests. Machine learning algorithms and systems include:

  • Concept Learning and the General-to-Specific Ordering
  • Decision Tree Learning
  • Artificial Neural Networks
  • Evaluating Hypotheses
  • Bayesian Learning
  • Computational Learning Theory
  • Instance-Based Learning
  • Genetic Algorithms
  • Learning Sets of Rules
  • Analytical Learning
  • Combining Inductive and Analytical Learning
  • Reinforcement Learning

Members

  • Patrick P.K. Chan, The Hong Kong Polytechnic University, Hong Kong
  • Shyi-Ming Chen, National Taiwan University of Science and Technology, Taiwan
  • M. Cheriet, Centre for Pattern Recognition and Machine Intelligence, Canada
  • Jyh-Horng Chou, National Kaohsiung First University of Science and Technology and National Kaohsiung University of Applied Sciences, Taiwan
  • Stan Klasa, Concordia University, Canada
  • Loi Lei Lai, City University London, UK
  • Seong-Whan Lee, Korea University, Korea
  • Xuelong Li, University of London, UK
  • Chih-Min Lin, Yuan-Ze University, Taiwan
  • Jiming Liu, Hong Kong Baptist University, Hong Kong
  • Wing Yin Ng, South China University of Technology, China
  • Vasile Palade, University of Oxford, UK
  • Daming Shi, Nanyang Technological University, Singapore
  • John Sum, National Chung Hsing University, Taiwan
  • Eric C.C. Tsang, The Hong Kong Polytechnic University, Hong Kong
  • Xizhao Wang, Hebei University, China
  • M. Arif Wani, Cal State University Bakersfield, USA
  • Yiming Ye, IBM T. J. Watson Research Center, USA
  • Xiaoqin Zeng, Hohai University, China
  • Ning Zhong, Maebashi Institute of Technology, Japan

Recent Activities

  • Co-sponsored 2015 International Conference on Machine Learning and Cybernetics (ICMLC).
  • Co-sponsored 2015 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR).
  • Co-sponsored 2014 International Conference on Machine Learning and Cybernetics (ICMLC).
  • Co-sponsored 2014 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR).
  • Organized a Special Session at SMC 2014.

Join Us

  • Interact with scientists and engineers in machine learning, which is a relatively new and rapidly growing research field and is widely used in many other research areas.
  • Participate in interesting conferences and workshops to exchange research ideas and results with scientists and engineers in the world.
  • Make friends from different regions of the world.

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