Machine Learning

Machine Learning

  • Kai-Zhu Huang
  • Haiqin Yang
  • Michael R. Lyu
Publisher:SpringerISBN 13: 9783540872351ISBN 10: 3540872353

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Know about the book -

Machine Learning is written by Kai-Zhu Huang and published by Springer. It's available with International Standard Book Number or ISBN identification 3540872353 (ISBN 10) and 9783540872351 (ISBN 13).

Machine Learning - Modeling Data Locally and Globally presents a novel and unified theory that tries to seamlessly integrate different algorithms. Specifically, the book distinguishes the inner nature of machine learning algorithms as either "local learning"or "global learning."This theory not only connects previous machine learning methods, or serves as roadmap in various models, but – more importantly – it also motivates a theory that can learn from data both locally and globally. This would help the researchers gain a deeper insight and comprehensive understanding of the techniques in this field. The book reviews current topics,new theories and applications. Kaizhu Huang was a researcher at the Fujitsu Research and Development Center and is currently a research fellow in the Chinese University of Hong Kong. Haiqin Yang leads the image processing group at HiSilicon Technologies. Irwin King and Michael R. Lyu are professors at the Computer Science and Engineering department of the Chinese University of Hong Kong.