Graph Embedding for Pattern Analysis (Record no. 56454)

000 -LEADER
fixed length control field 02960nam a22004935i 4500
001 - CONTROL NUMBER
control field 978-1-4614-4457-2
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112038.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 121117s2013 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781461444572
-- 978-1-4614-4457-2
082 04 - CLASSIFICATION NUMBER
Call Number 621.382
245 10 - TITLE STATEMENT
Title Graph Embedding for Pattern Analysis
300 ## - PHYSICAL DESCRIPTION
Number of Pages VIII, 260 p.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces -- Feature Grouping and Selection over an Undirected Graph -- Median Graph Computation by Means of Graph Embedding into Vector Spaces -- Patch Alignment for Graph Embedding -- Feature Subspace Transformations for Enhancing K-Means Clustering -- Learning with �1-Graph for High Dimensional Data Analysis -- Graph-Embedding Discriminant Analysis on Riemannian Manifolds for Visual Recognition -- A Flexible and Effective Linearization Method for Subspace Learning -- A Multi-Graph Spectral Approach for Mining Multi-Source Anomalies -- Graph Embedding for Speaker Recognition.
520 ## - SUMMARY, ETC.
Summary, etc 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 book which provides a comprehensive perspective of this field.
700 1# - AUTHOR 2
Author 2 Fu, Yun.
700 1# - AUTHOR 2
Author 2 Ma, Yunqian.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4614-4457-2
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- New York, NY :
-- Springer New York :
-- Imprint: Springer,
-- 2013.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Pattern recognition.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical engineering.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Communications Engineering, Networks.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Pattern Recognition.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence (incl. Robotics).
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Image and Speech Processing.
912 ## -
-- ZDB-2-ENG

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