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Reading List Support Vector Machines Hastie, Rosset, Tibshirani and Zhu (2004) The Entire Regularization Path for the Support Vector Machine , Journal of Machine Learning Research, 5, 1391-1415. Lin (2002) Support Vector Machines and the Bayes Rule in Classification, Data Mining and Knowledge Discovery, 6, 259-275. Pontil, Mukherjee, and Girosi (1998) On the Noise Model of Support Vector Machines Regression. Learning Theory Bartlett, Jordan and McAuliffe (2003) Large margin classifiers: convex loss, low noise, and convergence rates , in Advances in Neural Information Processing Systems, 16. Donoho (2004) For most large underdetermined systems of equations, the minimal L1-norm solution is also the sparset near-solution Manuscript, submitted. Donoho (2004) For most large underdetermined systems of linear equations, the minimal L1-norm near-solution approximates the sparset near-solution ,Manuscript, submitted. Poggio, Rifkin, Mukherjee and Niyogi (2004) General conditions for predicitivity in learning theory ,Nature, 428. Bousquet and Elisseeff (2002) Stability and Generation, JMLR, 428. Dimension Reduction Cook and Yin (2001) Dimension Reduction and Visualization in Discriminant Analysis. Model Selection Buhlmann and Yu (2005) Boosting, Model Selection, Lasso and Nonnegative Garrote. Yuan and Lin (2005) Model Selection and Estimation in Gaussian Graphical Model. Zou and Hastie (2005) Regularization and Variable Selection via the Elastic Net, Journal of the Royal Statistical Society, 67, 301-320. Tarigan and van de Geer (2005) Adaptivity of Support Vector Machines with l_1 Penalty. Zou, Hastie and Tibshirani (2005) On the ``Degree of Freedom'' of the Lasso. Zhao and Yu (2004) Boosted Lasso. Efron, Johnstone, Hastie and Tibshirani (2004) Least Angle Regression , The Annals of Statistics, 32, 407-499. Fan and Peng (2004) Nonconcave penalized likelihood with a diverging number of parameters , The Annals of Statistics, 32, 928-961. Tibshirani, Saunders, Rosset and Zhu (2005) Sparsity and smoothness via the fused Lasso, , Journal of the Royal Statistical Society: B, 67(1), 91-108. Mukherjee and Ding (2005) Learning Coordinate Covariances via Gradient, , Journal of Machine Learning Research, , submitted. Text Mining Genkin, Lewis and Madigan (2004) Large-Scale Bayesian Logistic Regression for Text Categorization. Algorithms Bousquet and Elisseeff (2002) Stability and Generation.

Last Updated: October 30, 2005