03022nam 2200589Ia 450 991043790330332120200520144314.01-283-91069-11-4614-4457-810.1007/978-1-4614-4457-2(CKB)2670000000312768(EBL)1081845(OCoLC)823729120(SSID)ssj0000811031(PQKBManifestationID)11456349(PQKBTitleCode)TC0000811031(PQKBWorkID)10846476(PQKB)10601339(DE-He213)978-1-4614-4457-2(MiAaPQ)EBC1081845(PPN)16830029X(EXLCZ)99267000000031276820121210d2013 uy 0engur|n|---|||||txtccrGraph embedding for pattern analysis /Yun Fu, Yunqian Ma, editors1st ed. 2013.New York Springerc20131 online resource (263 p.)Description based upon print version of record.1-4899-9062-3 1-4614-4456-X Includes bibliographical references.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 ℓ1-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.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.Pattern recognition systemsGraph theoryPattern recognition systems.Graph theory.006.3Fu Yun1762514Ma Yunqian1753446MiAaPQMiAaPQMiAaPQBOOK9910437903303321Graph embedding for pattern analysis4202496UNINA