Statistics

Empirical performance maximization for linear rank statistics NeurIPS 2008 Inferring rankings under constrained sensing NeurIPS 2008 Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of \boldmath$\ell_1$-regularized MLE NeurIPS 2008 On Bootstrapping the ROC Curve NeurIPS 2008 On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization NeurIPS 2008 A Kernel Statistical Test of Independence NeurIPS 2007 A Unified Near-Optimal Estimator For Dimension Reduction in l_α (0<α≤ 2) Using Stable Random Projections NeurIPS 2007 Combining PAC-Bayesian and Generic Chaining Bounds JMLR 2007 Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation NeurIPS 2007 Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization NeurIPS 2007 Near-Maximum Entropy Models for Binary Neural Representations of Natural Images NeurIPS 2007 On Ranking in Survival Analysis: Bounds on the Concordance Index NeurIPS 2007 Optimal ROC Curve for a Combination of Classifiers NeurIPS 2007 Stability Bounds for Non-i.i.d. Processes NeurIPS 2007 Testing for Homogeneity with Kernel Fisher Discriminant Analysis NeurIPS 2007 The Distribution Family of Similarity Distances NeurIPS 2007 A Kernel Method for the Two-Sample-Problem NeurIPS 2006 In Search of Non-Gaussian Components of a High-Dimensional Distribution JMLR 2006 PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NeurIPS 2006 Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds NeurIPS 2006 Analysis of Variance of Cross-Validation Estimators of the Generalization Error JMLR 2005 No Unbiased Estimator of the Variance of K-Fold Cross-Validation JMLR 2004