Learning Theory

Consistency and Localizability JMLR 2009 Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm JMLR 2009 Data-driven calibration of linear estimators with minimal penalties NeurIPS 2009 Discrete MDL Predicts in Total Variation NeurIPS 2009 Fast Learning from Non-i.i.d. Observations NeurIPS 2009 Fast, smooth and adaptive regression in metric spaces NeurIPS 2009 From PAC-Bayes Bounds to KL Regularization NeurIPS 2009 Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning NeurIPS 2009 Generalization Errors and Learning Curves for Regression with Multi-task Gaussian Processes NeurIPS 2009 Human Rademacher Complexity NeurIPS 2009 Information-theoretic lower bounds on the oracle complexity of convex optimization NeurIPS 2009 Kernels and learning curves for Gaussian process regression on random graphs NeurIPS 2009 Learning Acyclic Probabilistic Circuits Using Test Paths JMLR 2009 Learning Halfspaces with Malicious Noise JMLR 2009 Learning Permutations with Exponential Weights JMLR 2009 Local Rules for Global MAP: When Do They Work ? NeurIPS 2009 Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness NeurIPS 2009 Markov Properties for Linear Causal Models with Correlated Errors JMLR 2009 Measuring model complexity with the prior predictive NeurIPS 2009 Multi-Label Prediction via Compressed Sensing NeurIPS 2009 Noisy Generalized Binary Search NeurIPS 2009 On the Consistency of Feature Selection using Greedy Least Squares Regression JMLR 2009 On The Power of Membership Queries in Agnostic Learning JMLR 2009 On Uniform Deviations of General Empirical Risks with Unboundedness, Dependence, and High Dimensionality JMLR 2009 Potential-Based Agnostic Boosting NeurIPS 2009