Overview
Covers theoretical analysis and real-world applications for graph embedding
Examines subspace analysis with L1 graph
Describes graph-based inference on Riemannian manifolds for visual analysis
Includes supplementary material: sn.pub/extras
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (10 chapters)
Keywords
About this book
Reviews
From the reviews:
“The papers in this collection apply the methods elaborated in classical and algebraic graph theory to analyze patterns in various contexts. … the book will be easy for a researcher well versed in the theoretical fundamentals of the presented methods. … the editors have been able to structure the contents in an effective and interesting way. Therefore, I can recommend this volume as a useful reference for specialists in the field.” (Piotr Cholda, Computing Reviews, November, 2013)
Editors and Affiliations
About the editors
Dr. Yunqian Ma is a senior principal research scientist of Honeywell Labs at the Honeywell International Inc.
Bibliographic Information
Book Title: Graph Embedding for Pattern Analysis
Editors: Yun Fu, Yunqian Ma
DOI: https://doi.org/10.1007/978-1-4614-4457-2
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Science+Business Media New York 2013
Hardcover ISBN: 978-1-4614-4456-5Published: 17 November 2012
Softcover ISBN: 978-1-4899-9062-4Published: 13 December 2014
eBook ISBN: 978-1-4614-4457-2Published: 19 November 2012
Edition Number: 1
Number of Pages: VIII, 260
Topics: Communications Engineering, Networks, Pattern Recognition, Artificial Intelligence, Signal, Image and Speech Processing