Graph Embedding for Pattern Analysis is popular PDF and ePub book, written by Yun Fu in 2012-11-19, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Graph Embedding for Pattern Analysis can be Read Online from any device for your convenience.
Graph Embedding for Pattern Analysis Book PDF Summary
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.
Detail Book of Graph Embedding for Pattern Analysis PDF
- Author : Yun Fu
- Release : 19 November 2012
- Publisher : Springer Science & Business Media
- ISBN : 9781461444572
- Genre : Technology & Engineering
- Total Page : 264 pages
- Language : English
- PDF File Size : 12,9 Mb
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