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Add to basket23.5 cm x 15.5 cm, 584 g. X, 268 p. Hardcover. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Advanced Information and Knowledge Processing. Sprache: Englisch.
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by Springer International Publishing, 2018
ISBN 10: 3030007332 ISBN 13: 9783030007331
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
£ 124.16
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 readers' understanding from their similarity, and differences based on data organization and problemsettings, as well as the research goal.A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis 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.
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Published by Springer-Verlag New York Inc, 2019
ISBN 10: 3030007332 ISBN 13: 9783030007331
Language: English
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 278 pages. 9.25x6.10x0.79 inches. In Stock.
Seller: Mispah books, Redhill, SURRE, United Kingdom
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Published by Springer International Publishing, 2018
ISBN 10: 3030007332 ISBN 13: 9783030007331
Language: English
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Broadens your understanding of multi-view data analysisExplains how to design an effective multi-view data representation modelReinforces multi-view representation principles with real-world practices.
Published by Springer International Publishing Dez 2018, 2018
ISBN 10: 3030007332 ISBN 13: 9783030007331
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
£ 124.16
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Add to basketBuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 readers' understanding from their similarity, and differences based on data organization and problemsettings, as well as the research goal.A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis 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. 280 pp. Englisch.
Published by Springer International Publishing, Springer International Publishing Dez 2018, 2018
ISBN 10: 3030007332 ISBN 13: 9783030007331
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
£ 124.16
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Add to basketBuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 readers¿ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal.A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 280 pp. Englisch.
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Seller: Biblios, Frankfurt am main, HESSE, Germany
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