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Learning with Kernels: Support Vector Machines,

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


Learning.with.Kernels.Support.Vector.Machines.Regularization.Optimization.and.Beyond.pdf
ISBN: 0262194759,9780262194754 | 644 pages | 17 Mb


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
Publisher: The MIT Press




Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning). 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 (Adaptive Computation and Machine Learning Series). Learning with Kernels : Support Vector Machines, Regularization, Optimization, and Beyond. Learning with Kernels Support Vector Machines, Regularization, Optimization and Beyond. Conference on Computer Vision and Pattern Recognition (CVPR), 2001 ª Scholkopf and A. Learning with kernels support vector machines, regularization, optimization, and beyond. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , MIT Press, Cambridge, 2001. Bernhard Schlkopf, Alexander J. John Shawe-Taylor, Nello Cristianini. Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond (Adaptive Computation and Machine Learning) (Adaptive Computation and Machine Learning Series).

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