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Book Cover
Author Ding, Zhengming, author

Title Learning representation for multi-view data analysis : models and applications / Zhengming Ding, Handong Zhao, Yun Fu
Published Cham, Switzerland : Springer, [2019]
Online access available from:
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Description 1 online resource (xi, 268 pages)
Series Advanced information and knowledge processing
Advanced information and knowledge processing
Contents Introduction -- Multi-view Clustering with Complete Information -- Multi-view Clustering with Partial Information -- Multi-view Outlier Detection -- Multi-view Transformation Learning -- Zero-Shot Learning -- Missing Modality Transfer Learning -- Deep Domain Adaptation -- Deep Domain Generalization
Summary This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers' understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal. A comprehensive review exhaustively provides the key recent research on multi-view data analysis, id est, multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision
Bibliography Includes bibliographical references
Notes Online resource; title from digital title page (viewed on February 12, 2019)
Subject Learning models (Stochastic processes)
Machine learning
Learning models (Stochastic processes)
Machine learning.
Form Electronic book
Author Fu, Yun, author
Zhao, Handong, author
ISBN 3030007340