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

di Zhengming Ding (Autore)

Handong Zhao (Autore)

Yun Fu (Autore)

Springer Nature Switzerland AG, 2018

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.

• Autore: Zhengming Ding, Handong Zhao, Yun Fu
• Editore: Springer Nature Switzerland AG
• Collana: Advanced Information and Knowledge Processing
• Anno: 2018
• Rilegatura: Hardback
• Pagine: 268 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783030007331

Testo in English