The error rate of learning halfspaces using kernel-SVM

Kosaku Yosida. Functional Analysis. Springer-Verlag, Heidelberg, 1963.Eyal Kushilevitz and Yishay Mansour. Learning decision trees using the Fourier spectrum.In STOC, pages 455–464, May 1991.Nathan Linial, Yishay Mansour, and Noam Nisan. Constant depth circuits, Fourier transform,and learnability. In FOCS, pages 574–579, October 1989.P.M. Long and R.A. Servedio. Learning large-margin halfspaces with more malicious noise.In NIPS, 2011.J. Matousek. Lectures on discrete geometry, volume 212. Springer, 2002.V.D. Milman and G. Schechtman. Asymptotic Theory of Finite Dimensional Normed Spaces:Isoperimetric Inequalities in Riemannian Manifolds, volume 1200. Springer, 2002.F. Rosenblatt. The perceptron: A probabilistic model for information storage and organizationin the brain. Psychological Review, 65:386–407, 1958. (Reprinted in Neurocomputing(MIT Press, 1988).).S. Saitoh. Theory of reproducing kernels and its applications. Longman Scientific & TechnicalEngland, 1988.IJ Schoenberg. Positive definite functions on spheres. Duke. Math. J., 1942.B. Schölkopf, C. Burges, and A. Smola, editors. Advances in Kernel Methods - SupportVector Learning. MIT Press, 1998.S. Shalev-Shwartz, O. Shamir, and K. Sridharan. Learning kernel-based halfspaces with the0-1 loss. SIAM Journal on Computing, 40:1623–1646, 2011.I. Steinwart and A. Christmann. Support vector machines. Springer, 2008.R. Tibshirani. Regression shrinkage and selection via the lasso. J. Royal. Statist. Soc B., 58(1):267–288, 1996.V. N. Vapnik. Statistical Learning Theory. Wiley, 1998.Manfred K Warmuth and SVN Vishwanathan. Leaving the span. In Learning Theory, pages366–381. Springer, 2005.T. Zhang. Statistical behavior and consistency of classification methods based on convexrisk minimization. The Annals of Statistics, 32:56–85, 2004.44