Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond pdf free
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Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Alexander J. Smola, Bernhard Schlkopf
Learning.with.Kernels.Support.Vector.Machines.Regularization.Optimization.and.Beyond.pdf
ISBN: 0262194759,9780262194754 | 644 pages | 17 Mb
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond Alexander J. Smola, Bernhard Schlkopf
Publisher: The MIT Press
Weiterführende Literatur: Abney (2008). Applying Knowledge Management Techniques for Building Corporate Memories http://rapidshare.com/files/117882794/book56.rar. Conference on Computer Vision and Pattern Recognition (CVPR), 2001 ↑ Scholkopf and A. Schölkopf B, Smola AJ: Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond · MIT Press, 2001. "Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)" "Bernhard Schlkopf, Alexander J. Shannon CE: A mathematical theory of communication. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning series) - The MIT Press - ecs4.com. Support Vector Machines, Regularization, Optimization, and Beyond . Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. 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).