Statistical Learning

Inferring spike-timing-dependent plasticity from spike train data NeurIPS 2011 Information Rates and Optimal Decoding in Large Neural Populations NeurIPS 2011 Kernel Regression in the Presence of Correlated Errors JMLR 2011 k-NN Regression Adapts to Local Intrinsic Dimension NeurIPS 2011 Learning Attribute-weighted Voter Model over Social Networks ACML 2011 Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NeurIPS 2011 Learning large-margin halfspaces with more malicious noise NeurIPS 2011 Learning mixtures of Gaussians with maximum-a-posteriori oracle AISTATS 2011 Learning with the weighted trace-norm under arbitrary sampling distributions NeurIPS 2011 Linear-Time Estimators for Propensity Scores AISTATS 2011 Lower Bounds for Passive and Active Learning NeurIPS 2011 Minimax Localization of Structural Information in Large Noisy Matrices NeurIPS 2011 Minimum Description Length Penalization for Group and Multi-Task Sparse Learning JMLR 2011 Mixability is Bayes Risk Curvature Relative to Log Loss COLT 2011 Neyman-Pearson classification under a strict constraint COLT 2011 Noise Thresholds for Spectral Clustering NeurIPS 2011 On Causal Discovery with Cyclic Additive Noise Models NeurIPS 2011 On Learning Discrete Graphical Models using Group-Sparse Regularization AISTATS 2011 On the accuracy of l1-filtering of signals with block-sparse structure NeurIPS 2011 On Time Varying Undirected Graphs AISTATS 2011 On U-processes and clustering performance NeurIPS 2011 Operator Norm Convergence of Spectral Clustering on Level Sets JMLR 2011 Optimal aggregation of affine estimators COLT 2011 PAC-Bayesian Analysis of Contextual Bandits NeurIPS 2011 Quadratic Weighted Automata:Spectral Algorithm and Likelihood Maximization ACML 2011