Statistical Learning

Best Arm Identification for Contaminated Bandits JMLR 2019 Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance COLT 2019 Binarsity: a penalization for one-hot encoded features in linear supervised learning JMLR 2019 Black Box Quantiles for Kernel Learning AISTATS 2019 Bounding Uncertainty for Active Batch Selection AAAI 2019 Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy ICML 2019 Calibrated Approximate Bayesian Inference ICML 2019 Calibrated Model-Based Deep Reinforcement Learning ICML 2019 Causal Discovery in the Presence of Missing Data AISTATS 2019 Characterizing the Sample Complexity of Pure Private Learners JMLR 2019 Combining 3D Morphable Models: A Large Scale Face-And-Head Model CVPR 2019 Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters ICML 2019 Communication-Constrained Inference and the Role of Shared Randomness ICML 2019 Computing Full Conformal Prediction Set with Approximate Homotopy NeurIPS 2019 Conformalized Quantile Regression NeurIPS 2019 Conformal Prediction Under Covariate Shift NeurIPS 2019 Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon COLT 2019 Covariate-Powered Empirical Bayes Estimation NeurIPS 2019 Data-Dependence of Plateau Phenomenon in Learning with Neural Network --- Statistical Mechanical Analysis NeurIPS 2019 DBSCAN: Optimal Rates For Density-Based Cluster Estimation JMLR 2019 Deep Dominance - How to Properly Compare Deep Neural Models ACL 2019 Deep Factors for Forecasting ICML 2019 Deep learning generalizes because the parameter-function map is biased towards simple functions ICLR 2019 Deep Neural Networks Learn Non-Smooth Functions Effectively AISTATS 2019 Detecting Overfitting via Adversarial Examples NeurIPS 2019