Graph Embedding for Pattern Analysis

Yunqian Ma

ISBN 10: 1489990623 / ISBN 13: 9781489990624

Published by Springer New York, Springer New York Dez 2014, 2014

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 268 pp. Englisch.

Seller Inventory # 9781489990624

Bibliographic Details

• Title: Graph Embedding for Pattern Analysis
• Publisher: Springer New York, Springer New York Dez 2014
• Publication Date: 2014
• Language: English
• ISBN 10: 1489990623
• ISBN 13: 9781489990624
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 15D millimeters 235 millimeters width by 155 millimeters height by 15 millimeters depth
• Weight: 411 grams

About this title

Synopsis

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.

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.