Statistics

Cross-validation Confidence Intervals for Test Error NeurIPS 2020 Distributed Feature Screening via Componentwise Debiasing JMLR 2020 Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making ICML 2020 Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation ICLR 2020 Efficient Distance Approximation for Structured High-Dimensional Distributions via Learning NeurIPS 2020 Empirical Likelihood for Contextual Bandits NeurIPS 2020 Estimating Principal Components under Adversarial Perturbations COLT 2020 Estimating weighted areas under the ROC curve NeurIPS 2020 Hardness of Identity Testing for Restricted Boltzmann Machines and Potts models COLT 2020 Inference for Batched Bandits NeurIPS 2020 Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020 Information Theoretic Optimal Learning of Gaussian Graphical Models COLT 2020 Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms NeurIPS 2020 Kernel Conditional Moment Test via Maximum Moment Restriction UAI 2020 Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs JMLR 2020 Learning Structured Distributions From Untrusted Batches: Faster and Simpler NeurIPS 2020 Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications IJCAI 2020 Minimax Rate for Learning From Pairwise Comparisons in the BTL Model ICML 2020 Multiparameter Persistence Landscapes JMLR 2020 Multivariate Probability Calibration with Isotonic Bernstein Polynomials IJCAI 2020 NLPStatTest: A Toolkit for Comparing NLP System Performance AACL 2020 Non-asymptotic Analysis for Nonparametric Testing COLT 2020 Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses ACL 2020 On Learning Ising Models under Huber's Contamination Model NeurIPS 2020 On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration COLT 2020