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Learning with Kernels: Support Vector Machines,
Learning with Kernels: Support Vector Machines,

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



Download Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond




Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond Alexander J. Smola, Bernhard Schlkopf ebook
Publisher: The MIT Press
ISBN: 0262194759, 9780262194754
Format: pdf
Page: 644


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 (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. Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond (Adaptive Computation and Machine Learning) (Adaptive Computation and Machine Learning Series). Partly this is because a number of good ideas are overly associated with them: support/non-support training datums, weighting training data, discounting data, regularization, margin and the bounding of generalization error. Conference on Computer Vision and Pattern Recognition (CVPR), 2001 ↑ Scholkopf and A. Weiterführende Literatur: Abney (2008). 577, 580, Gaussian Processes for Machine Learning (MIT Press). Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond · MIT Press, 2001. Each is important even without the other: kernels are useful all over and support vector machines would be useful even if we restricted to the trivial identity kernel. In the machine learning imagination. 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. 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 Publisher The MIT Press Author(s) Alexander J. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning).

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