Robust representation data analytics par sheng (17 résultats)

Hardcover. Etat : Very Good. 1. Auflage. unread, with a mimimum of shelfwear.

hardcover. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Etat : New. Softcover reprint of the original 1st ed. 2017 edition NO-PA16APR2015-KAP.

Etat : New. pp. 220.

Hardcover. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Etat : Neu. Robust Representation for Data Analytics | Models and Applications | Sheng Li (u. a.) | Taschenbuch | Advanced Information and Knowledge Processing | xi | Englisch | 2018 | Springer | EAN 9783319867960 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Paperback. Etat : Brand New. reprint edition. 224 pages. 9.25x6.10x0.54 inches. In Stock.

Etat : new. Questo è un articolo print on demand.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Enriches understanding of robust feature representationsExplains how to develop robust data mining modelsReinforces robust representation principles with real-world practiceThis book introduces the concepts and models of robust repr.…

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Enriches understanding of robust feature representationsExplains how to develop robust data mining modelsReinforces robust representation principles with real-world practiceThis book introduces the concepts and models of robust repr.…

Etat : New. Print on Demand.

Etat : New. Print on Demand pp. 220.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 236 pp. Englisch.…

Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 236 pp. Englisch. …

Etat : New. PRINT ON DEMAND.

Etat : New. PRINT ON DEMAND pp. 220.