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

List 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.

Product details

• Assisted by: Marko Grobelnik (Editor), Steve Gunn (Editor), Craig Saunders (Editor), John Shawe-Taylor (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 16.05.2006
• EAN: 9783540341376
• ISBN: 978-3-540-34137-6
• No. of pages: 209
• Weight: 322 g
• Illustrations: X, 209 p.
• Series: Lecture Notes in Computer Science; Theoretical Computer Science and General Issues
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; C, Künstliche Intelligenz, Algorithms, Artificial Intelligence, Mustererkennung, Wahrscheinlichkeitsrechnung und Statistik, Maschinelles Sehen, Bildverstehen, Theoretische Informatik, Mathematik für Informatiker, computer science, Computer Vision, Theory of Computation, Image Processing and Computer Vision, pattern recognition, Computers, Mathematical & statistical software, Automated Pattern Recognition, Maths for computer scientists, Mathematical statistics, Probability and Statistics in Computer Science, Optical data processing, Algorithm Analysis and Problem Complexity, Image processing, Computation by Abstract Devices