Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond ebook
Par roth samuel le lundi, décembre 21 2015, 21:01 - Lien permanent
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond by Alexander J. Smola, Bernhard Schlkopf
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond Alexander J. Smola, Bernhard Schlkopf ebook
ISBN: 0262194759, 9780262194754
Page: 644
Publisher: The MIT Press
Format: pdf
Applying Knowledge Management Techniques for Building Corporate Memories http://rapidshare.com/files/117882794/book56.rar. Weiterführende Literatur: Abney (2008). Conference on Computer Vision and Pattern Recognition (CVPR), 2001 ↑ Scholkopf and A. Shannon CE: A mathematical theory of communication. Core Method: Kernel Methods for Pattern Analysis John Shawe-Taylor, Nello Cristianini Learning with Kernels : Support Vector Machines, Regularization, Optimizatio n, and Beyond Bernhard Schlkopf, Alexander J. Support Vector Machines, Regularization, Optimization, and Beyond . Schölkopf B, Smola AJ: Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning series) - The MIT Press - ecs4.com. Optimization: Convex Optimization Stephen Boyd, Lieven Vandenberghe Numerical Optimization Jorge Nocedal, Stephen Wright Optimization for Machine Learning Suvrit Sra, Sebastian Nowozin, Stephen J. Learning with Kernels Support Vector Machines, Regularization, Optimization and Beyond.