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portada Learning Representation for Multi-View Data Analysis
Type
Physical Book
Year
2019
Language
English
Pages
280
Format
Paperback
Dimensions
23.4 x 15.6 cm
ISBN13
9783030007355

Learning Representation for Multi-View Data Analysis

Handong Zhao;Yun Fu;Zhengming Ding (Author) · Springer Nature B.V. · Paperback

Learning Representation for Multi-View Data Analysis - Handong Zhao;Yun Fu;Zhengming Ding

New Book Imported to Austria
Delivery: 23 Jul - 31 Jul Shipping: 14 to 19 business days.
60,71 €
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60,71 €

Synopsis "Learning Representation for Multi-View Data Analysis"

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.

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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.

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