Learning Representation for Multi-View Data Analysis: Models and Applications (Advanced Information and Knowledge Processing) - Tapa dura

Zhao, Handong; Fu, Yun; Ding, Zhengming

 
9783030007331: Learning Representation for Multi-View Data Analysis: Models and Applications (Advanced Information and Knowledge Processing)
Tapa dura
ISBN 10: 3030007332 ISBN 13: 9783030007331
Editorial: Springer, 2018

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2018
Idioma
Inglés
ISBN 10 
3030007332
ISBN 13 
9783030007331
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
280
Contacto del fabricante
no disponible
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