[PDF.91iq] Regularization, Optimization, Kernels, and Support Vector Machines (Chapman & Hall/Crc Machine Learning & Pattern Recognition Series)

Regularization, Optimization, Kernels, and Support Vector Machines (Chapman & Hall/Crc Machine Learning & Pattern Recognition Series)

[PDF.bt16] Regularization, Optimization, Kernels, and Support Vector Machines (Chapman & Hall/Crc Machine Learning & Pattern Recognition Series)

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 | #3470404 in Books |  2014-10-23 | Original language:English | PDF # 1 |  9.00 x1.40 x6.40l,.0 | File type: PDF | 525 pages

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||About the Author||Johan A.K. Suykens is a professor at Katholieke Universiteit Leuven, Belgium, where he obtained a degree in electro-mechanical engineering and a Ph.D in applied sciences. He has been a visiting postdoctoral researcher at the Un

Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and large-scale optimization, kernel methods, and support vector machines. Consisting of 21 chapters authored by leading researchers in machine learning, this comprehen...

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