Mon premier blog

Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond Alexander J. Smola, Bernhard Schlkopf
Publisher: The MIT Press

Applying Knowledge Management Techniques for Building Corporate Memories http://rapidshare.com/files/117882794/book56.rar. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond · MIT Press, 2001. Schölkopf B, Smola AJ: Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond. John Shawe-Taylor, Nello Cristianini. Conference on Computer Vision and Pattern Recognition (CVPR), 2001 ↑ Scholkopf and A. 577, 580, Gaussian Processes for Machine Learning (MIT Press). Weiterführende Literatur: Abney (2008). 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. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning Series). Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , MIT Press, Cambridge, 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Shannon CE: A mathematical theory of communication. Learning with Kernels Support Vector Machines, Regularization, Optimization and Beyond. Will Read Data Mining: Practical Machine Learning Tools and Techniques 难度低使用 Kernel. Learning with Kernels : Support Vector Machines, Regularization, Optimization, and Beyond. Bernhard Schlkopf, Alexander J.