Learning Representation for Multi-View Data Analysis Learning Representation for Multi-View Data Analysis
Advanced Information and Knowledge Processing

Learning Representation for Multi-View Data Analysis

Models and Applications

Zhengming Ding and Others
    • $139.99
    • $139.99

Publisher Description

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.

GENRE
Computing & Internet
RELEASED
2018
6 December
LANGUAGE
EN
English
LENGTH
278
Pages
PUBLISHER
Springer International Publishing
SELLER
Springer Nature B.V.
SIZE
32.6
MB

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