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
Format: pdf
Page: 644
Publisher: The MIT Press
ISBN: 0262194759, 9780262194754

Learning with Kernels : Support Vector Machines, Regularization, Optimization, and Beyond. Novel indices characterizing graphical models of residues were B. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning Series). "Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)" "Bernhard Schlkopf, Alexander J. Support Vector Machines, Regularization, Optimization, and Beyond . 577, 580, Gaussian Processes for Machine Learning (MIT Press). Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond Publisher The MIT Press Author(s) Alexander J. Schölkopf B, Smola AJ: Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond. John Shawe-Taylor, Nello Cristianini. Weiterführende Literatur: Abney (2008). Machine learning was applied to a challenging and biologically significant protein classification problem: the prediction of avonoid UGT acceptor regioselectivity from primary sequence. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning series) - The MIT Press - ecs4.com. Shannon CE: A mathematical theory of communication. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond, The MIT Press, 1st edition, 2001. Optimization: Convex Optimization Stephen Boyd, Lieven Vandenberghe Numerical Optimization Jorge Nocedal, Stephen Wright Optimization for Machine Learning Suvrit Sra, Sebastian Nowozin, Stephen J. Bernhard Schlkopf, Alexander J. 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. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond · MIT Press, 2001.