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Item Details
Title: GRAPH EMBEDDING FOR PATTERN ANALYSIS
By: Yun Fu (Editor), Yunqian Ma (Editor)
Format: Hardback

List price: £119.99


We currently do not stock this item, please contact the publisher directly for further information.

ISBN 10: 146144456X
ISBN 13: 9781461444565
Publisher: SPRINGER-VERLAG NEW YORK INC.
Pub. date: 17 November, 2012
Edition: 2013 ed.
Pages: 260
Description: 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.
Synopsis: 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.
Illustrations: 45 Tables, black and white; VIII, 260 p.
Publication: US
Imprint: Springer-Verlag New York Inc.
Returns: Returnable
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