Graph Embedding for Pattern Analysis

Graph Embedding for Pattern Analysis
Author :
Publisher : Springer Science & Business Media
Total Pages : 264
Release :
ISBN-10 : 9781461444572
ISBN-13 : 1461444578
Rating : 4/5 (578 Downloads)

Book Synopsis Graph Embedding for Pattern Analysis by : Yun Fu

Download or read book Graph Embedding for Pattern Analysis written by Yun Fu and published by Springer Science & Business Media. This book was released on 2012-11-19 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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