E-Book, Englisch, 268 Seiten
Ding / Zhao / Fu Learning Representation for Multi-View Data Analysis
1. Auflage 2018
ISBN: 978-3-030-00734-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Models and Applications
E-Book, Englisch, 268 Seiten
Reihe: Advanced Information and Knowledge Processing
ISBN: 978-3-030-00734-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
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.
