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  • Book
  • © 2008

Machine Learning

Modeling Data Locally and Globally

Authors:

  • New unified theory
  • Detailed graphic illustration
  • Empirical validation for each model

Part of the book series: Advanced Topics in Science and Technology in China (ATSTC)

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About this book

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 departmentof the Chinese University of Hong Kong.

Authors and Affiliations

  • Dept. of CSE, Chinese Univ. of Hong Kong, Shatin. N.T. HK, China

    Kaizhu Huang, Haiqin Yang, Irwin King, Michael Lyu

Bibliographic Information

Buy it now

Buying options

eBook USD 139.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Other ways to access