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

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

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 reader...

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Bibliographic Details
Main Authors: Ding, Zhengming (Author, http://id.loc.gov/vocabulary/relators/aut), Zhao, Handong (http://id.loc.gov/vocabulary/relators/aut), Fu, Yun (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
Edition:1st ed. 2019.
Series:Advanced Information and Knowledge Processing,
Subjects:
Data mining.
Artificial intelligence.
Pattern recognition.
Data Mining and Knowledge Discovery.
Artificial Intelligence.
Pattern Recognition.
Online Access:Full Text via HEAL-Link
Table of Contents:
  • Introduction
  • Multi-view Clustering with Complete Information
  • Multi-view Clustering with Partial Information
  • Multi-view Outlier Detection
  • Multi-view Transformation Learning
  • Zero-Shot Learning
  • Missing Modality Transfer Learning
  • Deep Domain Adaptation
  • Deep Domain Generalization. .

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