Multiview Machine Learning for Data Analysis

Authors: Sun, S., Mao, L., Dong, Z., Wu, L.

  • The first comprehensive and in-depth book on multiview machine learning
  • Blends theory and practice, presenting state-of-the-art methodologiesEquips readers to handle complex data analysis tasks with advanced machine learning tools
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eBook  
  • ISBN 978-981-13-3029-2
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover ca. $149.99
price for USA in USD
  • Due: May 14, 2019
  • ISBN 978-981-13-3028-5
  • Free shipping for individuals worldwide
About this book

This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpinnings and great practical success. This book describes the models and algorithms of multiview learning in real data analysis. Incorporating multiple views to improve the generalization performance, multiview learning is also known as data fusion or data integration from multiple feature sets. This self-contained book is applicable for multi-modal learning research, and requires minimal prior knowledge of the basic concepts in the field. It is also a valuable reference resource for researchers working in the field of machine learning and also those in various application domains.  

About the authors

Shiliang Sun received his Ph.D. degree in pattern recognition and intelligent systems from Tsinghua University, Beijing, China, in 2007. He is now a professor at the Department of Computer Science and Technology and the head of the Pattern Recognition and Machine Learning Research Group, East China Normal University, Shanghai, China. His current research interests include multiview learning, kernel methods, learning theory, probabilistic models, approximate inference, and sequential modeling. He has published 150+ research articles at peer-reviewed journals and international conferences. Prof. Sun is on the editorial board of several international journals, including IEEE Transactions on Neural Networks and Learning Systems, Information Fusion, and Pattern Recognition.

Liang Mao is a senior Ph.D. student at the Department of Computer Science and Technology and the Pattern Recognition and Machine Learning Research Group, East China Normal University, Shanghai, China. His main research interest is multiview learning and probabilistic models. 

Buy this book

eBook  
  • ISBN 978-981-13-3029-2
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover ca. $149.99
price for USA in USD
  • Due: May 14, 2019
  • ISBN 978-981-13-3028-5
  • Free shipping for individuals worldwide

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Bibliographic Information

Bibliographic Information
Book Title
Multiview Machine Learning for Data Analysis
Authors
Copyright
2019
Publisher
Springer Singapore
Copyright Holder
Springer Nature Singapore Pte Ltd.
eBook ISBN
978-981-13-3029-2
Hardcover ISBN
978-981-13-3028-5
Edition Number
1
Number of Illustrations and Tables
40 illustrations in colour
Topics