Téléchargez le livre : Robust Representation for Data Analytics

Robust Representation for Data Analytics

Models and Applications de

,

Éditeur :

Springer


Collection :

Advanced Information and Knowledge Processing

Paru le : 2017-08-09

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Description
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 robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary.
Leveraging the theory of low-rank and sparse modeling, the authors develop robust feature representations under various learning paradigms, including unsupervised learning, supervised learning, semi-supervised learning, multi-view learning, transfer learning, and deep learning. Robust Representations for Data Analytics 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.
Pages
224 pages
Collection
Advanced Information and Knowledge Processing
Parution
2017-08-09
Marque
Springer
EAN papier
9783319601755
EAN PDF
9783319601762
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
22
Taille du fichier
5028 Ko
Prix
116,04 €
EAN EPUB
9783319601762
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
22
Taille du fichier
2970 Ko
Prix
116,04 €

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