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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

Conference on Computer Vision and Pattern Recognition (CVPR), 2001 ↑ Scholkopf and A. We use the support vector regression (SVR) method to predict the use of an embryo. Learning with kernels support vector machines, regularization, optimization, and beyond. Learning with Kernels : Support Vector Machines, Regularization, Optimization, and Beyond. Smola, Learning with Kernels—Support Vector Machines, Regularization, Optimization and Beyond , MIT Press Series, 2002. Learning with Kernels Support Vector Machines, Regularization, Optimization and Beyond. 577, 580, Gaussian Processes for Machine Learning (MIT Press). Bernhard Schlkopf, Alexander J. Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond (Adaptive Computation and Machine Learning) (Adaptive Computation and Machine Learning Series). Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond Publisher The MIT Press Author(s) Alexander J. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning). Weiterführende Literatur: Abney (2008). Will Read Data Mining: Practical Machine Learning Tools and Techniques 难度低使用 Kernel. John Shawe-Taylor, Nello Cristianini. "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 . Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond.