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ShiliangSun· LiangMao· ZiangDong·
LidanWu
Multiview
Machine
Learning

Multiview Machine Learning

Shiliang Sun
•
Liang Mao
•
Ziang Dong
•
Lidan Wu
Multiview Machine Learning
123

Shiliang Sun
Department of Computer Science
and Technology
East China Normal University
Shanghai, China
Liang Mao
Department of Computer Science
and Technology
East China Normal University
Shanghai, China
Ziang Dong
Department of Computer Science
and Technology
East China Normal University
Shanghai, China
Lidan Wu
Department of Computer Science
and Technology
East China Normal University
Shanghai, China
ISBN 978-981-13-3028-5 ISBN 978-981-13-3029-2 (eBook)
https://doi.org/10.1007/978-981-13-3029-2
Library of Congress Control Number: 2018963292
© Springer Nature Singapore Pte Ltd. 2019
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part
of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,
recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission
or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar
methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this
publication does not imply, even in the absence of a specific statement, that such names are exempt from
the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this
book are believed to be true and accurate at the date of publication. Neither the publisher nor the
authors or the editors give a warranty, express or implied, with respect to the material contained herein or
for any errors or omissions that may have been made. The publisher remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd.
The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721,
Singapore

Preface
During the past two decades, multiview learning as an emerging direction in
machine learning became a prevailing research topic in artificial intelligence (AI).
Its success and popularity were largely motivated by the fact that real-world
applications ge nerate various data as different views while people try to manipulate
and integrate those data for performance improvements. In the data era, this situ-
ation will continue. We think the multiview learning research will be active for a
long time, and further development and in-depth studies are needed to make it more
effective and practical.
In 2013, a review paper of mine, entitled “A Survey of Multi-view Machine
Learning” (Neural Computing and Applications, 2013), was published. It generates
a good dissemination and promotion of multiview learning and has been well cited.
Since then, much more research has been developed. This book aims to provide an
in-depth and comprehensive introduction to multiview learning and hope to be
helpful for AI researchers and practitioners.
I have been working in the machine learning area for more than 15 years. Most
of my work introduced in this book was completed after I graduated from Tsinghua
University and joined East China Normal University in 2007. And we also include
many important and representative works from other researchers to make the book
content complete and comprehensive. Due to space and time limits, we may not be
able to include all relevant works.
I owe many thanks to the past and current members of my Pattern Recognition
and Machine Learning Research Group, East China Normal University, for their
hard work to make research done in time. The relationship between me and them is
not just profes sors and students, but also comrades-in-arms.
Shanghai, China Shiliang Sun
September 2018
v
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