Subspace, Latent Structure and Feature Selection: Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers / Edition 1 by Craig Saunders | 9783540341376 | Paperback | Barnes & Noble
Subspace, Latent Structure and Feature Selection: Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers / Edition 1

Subspace, Latent Structure and Feature Selection: Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers / Edition 1

by Craig Saunders
     
 

ISBN-10: 3540341374

ISBN-13: 9783540341376

Pub. Date: 07/06/2006

Publisher: Springer Berlin Heidelberg

This book constitutes the thoroughly refereed post-proceedings of the PASCAL (pattern analysis, statistical modelling and computational learning) Statistical and Optimization Perspectives Workshop on Subspace, Latent Structure and Feature Selection techniques, SLSFS 2005, held in Bohinj, Slovenia in February 2005. The 9 revised full papers presented together with 5

Overview

This book constitutes the thoroughly refereed post-proceedings of the PASCAL (pattern analysis, statistical modelling and computational learning) Statistical and Optimization Perspectives Workshop on Subspace, Latent Structure and Feature Selection techniques, SLSFS 2005, held in Bohinj, Slovenia in February 2005. The 9 revised full papers presented together with 5 invited papers were carefully selected during two rounds of reviewing and improvement for inclusion in the book. The papers reflect the key approaches that have been developed for subspace identification and feature selection using dimension reduction techniques, subspace methods, random projection methods, statistical analysis methods, Bayesian approaches to feature selection, latent structure analysis/probabilistic LSA, and optimisation methods.

Product Details

ISBN-13:
9783540341376
Publisher:
Springer Berlin Heidelberg
Publication date:
07/06/2006
Series:
Lecture Notes in Computer Science / Theoretical Computer Science and General Issues Series, #3940
Edition description:
2006
Pages:
209
Product dimensions:
0.47(w) x 6.14(h) x 9.21(d)

Related Subjects

Table of Contents

Invited 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.

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