Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Journal of the American Statistical AssociationPublished 1 June 2003
Christopher K. I. Williams
Citations4,326
SJR quartileQ1
SJR score4.10
SNIP3.08
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TL;DR
Learning with Kernels provides an introduction to SVMs and related kernel methods that provide all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms.
Abstract
(2003). Learning With Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Journal of the American Statistical Association: Vol. 98, No. 462, pp. 489-489.
Keywords
Computer Science