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

• 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.

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...

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. .