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Majestic Books, Hounslow, Royaume-Uni
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Vendeur AbeBooks depuis 19 janvier 2007
Print on Demand pp. 268. N° de réf. du vendeur 356075475
This book presents advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph and graph in vector spaces, and describes their real-world applications.
À propos de l?auteur:
Dr. Yun Fu is a professor at the State University of New York at Buffalo
Dr. Yunqian Ma is a senior principal research scientist of Honeywell Labs at the Honeywell International Inc.
Titre : Graph Embedding for Pattern Analysis
Éditeur : Springer
Date d'édition : 2014
Reliure : Couverture souple
Etat : New
Vendeur : Brook Bookstore On Demand, Napoli, NA, Italie
Etat : new. Questo è un articolo print on demand. N° de réf. du vendeur 333abc9cc0001ccca344ea13860536e8
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers theoretical analysis and real-world applications for graph embedding Examines subspace analysis with L1 graph Describes graph-based inference on Riemannian manifolds for visual analysisDr. Yun Fu is a professor at the State U. N° de réf. du vendeur 4213082
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Graph Embedding for Pattern Analysis | Yunqian Ma (u. a.) | Taschenbuch | viii | Englisch | 2014 | Springer New York | EAN 9781489990624 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 104963663
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the latest advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph, and graph in vector spaces. Real-world applications of these theories are spanned broadly in dimensionality reduction, subspace learning, manifold learning, clustering, classification, and feature selection. A selective group of experts contribute to different chapters of this book which provides a comprehensive perspective of this field. 268 pp. Englisch. N° de réf. du vendeur 9781489990624
Quantité disponible : 2 disponible(s)
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the latest advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph, and graph in vector spaces. Real-world applications of these theories are spanned broadly in dimensionality reduction, subspace learning, manifold learning, clustering, classification, and feature selection. A selective group of experts contribute to different chapters of this book which provides a comprehensive perspective of this field.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 268 pp. Englisch. N° de réf. du vendeur 9781489990624
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Graph Embedding for Pattern Recognition covers theory methods, computation, and applications widely used in statistics, machine learning, image processing, and computer vision. This book presents the latest advances in graph embedding theories, such as nonlinear manifold graph, linearization method, graph based subspace analysis, L1 graph, hypergraph, undirected graph, and graph in vector spaces. Real-world applications of these theories are spanned broadly in dimensionality reduction, subspace learning, manifold learning, clustering, classification, and feature selection. A selective group of experts contribute to different chapters of this book which provides a comprehensive perspective of this field. N° de réf. du vendeur 9781489990624
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9781489990624_new
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Vendeur : Chiron Media, Wallingford, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur 6666-IUK-9781489990624
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 268 pages. 9.30x6.20x0.63 inches. In Stock. N° de réf. du vendeur x-1489990623
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Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Paperback. Etat : Like New. Like New. book. N° de réf. du vendeur ERICA77314899906236
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