Statistical Learning

Modelling motion primitives and their timing in biologically executed movements NeurIPS 2007 Near-Maximum Entropy Models for Binary Neural Representations of Natural Images NeurIPS 2007 Nonlinear Estimators and Tail Bounds for Dimension Reduction in l1 Using Cauchy Random Projections JMLR 2007 Optimal ROC Curve for a Combination of Classifiers NeurIPS 2007 PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers JMLR 2007 Progressive mixture rules are deviation suboptimal NeurIPS 2007 Random Projections for Manifold Learning NeurIPS 2007 Receptive Fields without Spike-Triggering NeurIPS 2007 Separating Models of Learning from Correlated and Uncorrelated Data JMLR 2007 SpAM: Sparse Additive Models NeurIPS 2007 Stability Bounds for Non-i.i.d. Processes NeurIPS 2007 Statistical Analysis of Semi-Supervised Regression NeurIPS 2007 Statistical Consistency of Kernel Canonical Correlation Analysis JMLR 2007 Testing for Homogeneity with Kernel Fisher Discriminant Analysis NeurIPS 2007 The Distribution Family of Similarity Distances NeurIPS 2007 The Tradeoffs of Large Scale Learning NeurIPS 2007 Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations NeurIPS 2007 Value Regularization and Fenchel Duality JMLR 2007 Variational inference for Markov jump processes NeurIPS 2007 Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems JMLR 2006 Active learning for misspecified generalized linear models NeurIPS 2006 AdaBoost is Consistent NeurIPS 2006 A Kernel Method for the Two-Sample-Problem NeurIPS 2006 A Linear Non-Gaussian Acyclic Model for Causal Discovery JMLR 2006 An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments NeurIPS 2006