Statistical Learning

Collaborative Filtering with the Trace Norm: Learning, Bounding, and Transducing COLT 2011 Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NeurIPS 2011 Computationally Efficient Sufficient Dimension Reduction via Squared-Loss Mutual Information ACML 2011 Confidence Sets for Network Structure NeurIPS 2011 Continuous-Time Regression Models for Longitudinal Networks NeurIPS 2011 Demixed Principal Component Analysis NeurIPS 2011 Differentially Private M-Estimators NeurIPS 2011 DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model JMLR 2011 Dynamical segmentation of single trials from population neural data NeurIPS 2011 Efficient inference in matrix-variate Gaussian models with \iid observation noise NeurIPS 2011 Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression NeurIPS 2011 Empirical models of spiking in neural populations NeurIPS 2011 Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure AISTATS 2011 Estimating beta-mixing coefficients AISTATS 2011 Generalization Bound for Infinitely Divisible Empirical Process AISTATS 2011 Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss NeurIPS 2011 Generalized TD Learning JMLR 2011 Greedy Model Averaging NeurIPS 2011 Heavy-tailed Distances for Gradient Based Image Descriptors NeurIPS 2011 High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions NeurIPS 2011 High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity NeurIPS 2011 How biased are maximum entropy models? NeurIPS 2011 Hyper-Sparse Optimal Aggregation JMLR 2011 In All Likelihood, Deep Belief Is Not Enough JMLR 2011 Inductive reasoning about chimeric creatures NeurIPS 2011