Statistical Learning

Meta-Gaussian Information Bottleneck NeurIPS 2012 Minimax hypothesis testing for curve registration AISTATS 2012 Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming JMLR 2012 Minimax rates for homology inference AISTATS 2012 Mixability in Statistical Learning NeurIPS 2012 Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions NeurIPS 2012 Multi-Task Averaging NeurIPS 2012 Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics JMLR 2012 Nonconvex Penalization Using Laplace Exponents and Concave Conjugates NeurIPS 2012 Nonparametric Estimation of Conditional Information and Divergences AISTATS 2012 Nonparametric Reduced Rank Regression NeurIPS 2012 On Estimation and Selection for Topic Models AISTATS 2012 Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits AISTATS 2012 On Ranking and Generalization Bounds JMLR 2012 On the Sample Complexity of Robust PCA NeurIPS 2012 Optimal kernel choice for large-scale two-sample tests NeurIPS 2012 Optimal Neural Tuning Curves for Arbitrary Stimulus Distributions: Discrimax, Infomax and Minimum L_p Loss NeurIPS 2012 PAC-Bayes Bounds with Data Dependent Priors JMLR 2012 PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model COLT 2012 Privacy Aware Learning NeurIPS 2012 Proper losses for learning from partial labels NeurIPS 2012 Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders NeurIPS 2012 Random Design Analysis of Ridge Regression COLT 2012 Reconstruction from Anisotropic Random Measurements COLT 2012 Reducing statistical time-series problems to binary classification NeurIPS 2012