Overview
- 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.
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Keywords
Table of contents (8 chapters)
Authors and Affiliations
Bibliographic Information
Book Title: Machine Learning
Book Subtitle: Modeling Data Locally and Globally
Authors: Kaizhu Huang, Haiqin Yang, Irwin King, Michael Lyu
Series Title: Advanced Topics in Science and Technology in China
DOI: https://doi.org/10.1007/978-3-540-79452-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
eBook ISBN: 978-3-540-79452-3Published: 24 September 2008
Series ISSN: 1995-6819
Series E-ISSN: 1995-6827
Edition Number: 1
Number of Pages: X, 169
Number of Illustrations: 53 b/w illustrations
Additional Information: Jointly published with Zhejiang University Press
Topics: Pattern Recognition, Information Storage and Retrieval, Data Mining and Knowledge Discovery