Graph Embedding for Pattern Analysis
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 boo…
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Produktdetails
Weitere Autoren: Ma, Yunqian (Hrsg.)
- ISBN: 978-1-4899-9062-4
- EAN: 9781489990624
- Produktnummer: 17376924
- Verlag: Springer New York
- Sprache: Englisch
- Erscheinungsjahr: 2014
- Seitenangabe: 268 S.
- Masse: H23.5 cm x B15.5 cm x D1.4 cm 411 g
- Auflage: 2013
- Abbildungen: Paperback
- Gewicht: 411
Über 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.
13 weitere Werke von Yun (Hrsg.) Fu:
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