Graph Embedding for Pattern Analysis (Paperback)

Graph Embedding for Pattern Analysis By Yun Fu (Editor), Yunqian Ma (Editor) Cover Image
By Yun Fu (Editor), Yunqian Ma (Editor)
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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.

About the Author

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.

Product Details
ISBN: 9781489990624
ISBN-10: 1489990623
Publisher: Springer
Publication Date: December 13th, 2014
Pages: 260
Language: English