Graph Embedding for Pattern Analysis - Softcover

Softcover

ISBN 10: 1489990623 ISBN 13: 9781489990624

Verlag: Springer, 2014

Inhaltsangabe

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.

Über diesen Titel

Über die Autorin bzw. den Autor

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.

Von der hinteren Coverseite

Graph Embedding for Pattern Analysis 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.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2014
• Sprache: Englisch
• ISBN 10: 1489990623
• ISBN 13: 9781489990624
• Einband: Taschenbuch
• Anzahl der Seiten: 268
• Herausgeber: Fu Yun, Ma Yunqian
• Kontakt zum Hersteller: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Deutschland