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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Ding, Zhengming (Συγγραφέας, 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)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:Advanced Information and Knowledge Processing,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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. .