{"product_id":"9783540341376","title":"Subspace, Latent Structure and Feature Selection : Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 20","description":"\u003cp\u003eInvited Contributions.- Discrete Component Analysis.- Overview and Recent Advances in Partial Least Squares.- Random Projection, Margins, Kernels, and Feature-Selection.- Some Aspects of Latent Structure Analysis.- Feature Selection for Dimensionality Reduction.- Contributed Papers.- Auxiliary Variational Information Maximization for Dimensionality Reduction.- Constructing Visual Models with a Latent Space Approach.- Is Feature Selection Still Necessary?.- Class-Specific Subspace Discriminant Analysis for High-Dimensional Data.- Incorporating Constraints and Prior Knowledge into Factorization Algorithms - An Application to 3D Recovery.- A Simple Feature Extraction for High Dimensional Image Representations.- Identifying Feature Relevance Using a Random Forest.- Generalization Bounds for Subspace Selection and Hyperbolic PCA.- Less Biased Measurement of Feature Selection Benefits.\u003c\/p\u003e","brand":"Springer-Verlag New York Inc","offers":[{"title":"Default Title","offer_id":48765066215659,"sku":"00000_00000_00000_00000","price":100.69,"currency_code":"SGD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0758\/4484\/5803\/files\/9783540341376-1.jpg?v=1783558131","url":"https:\/\/kinokuniya.com.sg\/ja\/products\/9783540341376","provider":"Books Kinokuniya Singapore","version":"1.0","type":"link"}