Téléchargez le livre : Graph Embedding for Pattern Analysis

Graph Embedding for Pattern Analysis

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Springer


Paru le : 2012-11-19

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Description
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.
Pages
260 pages
Collection
n.c
Parution
2012-11-19
Marque
Springer
EAN papier
9781461444565
EAN PDF
9781461444572
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
26
Taille du fichier
7496 Ko
Prix
95,39 €

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