Learning Representation for Multi-View Data Analysis : Models and Applications

Ding, Zhengming; Zhao, Handong; Fu, Yun

ISBN 10: 3030007332 / ISBN 13: 9783030007331

Published by Springer, 2018

About this Item

Seller Inventory # 26376483319

Bibliographic Details

• Title: Learning Representation for Multi-View Data Analysis : Models and Applications
• Publisher: Springer
• Publication Date: 2018
• Language: English
• ISBN 10: 3030007332
• ISBN 13: 9783030007331
• Binding: Hardcover
• Condition: New

About this title

Synopsis

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, i.e., 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.