Statistical Learning

Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation NeurIPS 2013 Modeling Information Propagation with Survival Theory ICML 2013 Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition NeurIPS 2013 Moment-based Uniform Deviation Bounds for k-means and Friends NeurIPS 2013 More data speeds up training time in learning halfspaces over sparse vectors NeurIPS 2013 Multi-Class Classification with Maximum Margin Multiple Kernel ICML 2013 Multiple-source cross-validation ICML 2013 Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic NeurIPS 2013 Near-Optimal Bounds for Cross-Validation via Loss Stability ICML 2013 Nonparametric Sparsity and Regularization JMLR 2013 One-Pass AUC Optimization ICML 2013 On model selection consistency of penalized M-estimators: a geometric theory NeurIPS 2013 On the Mutual Nearest Neighbors Estimate in Regression JMLR 2013 On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation NeurIPS 2013 On the Sample Complexity of Subspace Learning NeurIPS 2013 On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance ICML 2013 Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization ICML 2013 PAC-Bayes-Empirical-Bernstein Inequality NeurIPS 2013 Parsing epileptic events using a Markov switching process model for correlated time series ICML 2013 Passive Learning with Target Risk COLT 2013 Permutation estimation and minimax rates of identifiability AISTATS 2013 Predictive Correlation Screening: Application to Two-stage Predictor Design in High Dimension AISTATS 2013 Predictive PAC Learning and Process Decompositions NeurIPS 2013 Principal Component Analysis on non-Gaussian Dependent Data ICML 2013 Probabilistic Principal Geodesic Analysis NeurIPS 2013