Robust Representation for Data Analytics Models and Applications

Robust Representation for Data Analytics Models and Applications / by Sheng Li, Yun Fu.

This book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection, etc. Three types of...

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Bibliographic Details
Main Authors: Li, Sheng (Author), Fu, Yun (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
Edition:1st ed. 2017.
Series:Advanced Information and Knowledge Processing,
Springer eBook Collection.
Subjects:
Data mining.
Artificial intelligence.
Pattern recognition.
Optical data processing.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Introduction
  • Fundamentals of Robust Representations
  • Part 1: Robust Representation Models
  • Robust Graph Construction
  • Robust Subspace Learning
  • Robust Multi-View Subspace Learning
  • Part 11: Applications
  • Robust Representations for Collaborative Filtering
  • Robust Representations for Response Prediction
  • Robust Representations for Outlier Detection
  • Robust Representations for Person Re-Identification
  • Robust Representations for Community Detection
  • Index.

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