Statistical Learning

The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records MLHC 2019 The non-parametric bootstrap and spectral analysis in moderate and high-dimension AISTATS 2019 The Optimal Approximation Factor in Density Estimation COLT 2019 Theoretically Principled Trade-off between Robustness and Accuracy ICML 2019 The Rationality of Semantic Change ACL 2019 The Relative Complexity of Maximum Likelihood Estimation, MAP Estimation, and Sampling COLT 2019 The spiked matrix model with generative priors NeurIPS 2019 Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds ICML 2019 Tossing Coins Under Monotonicity AISTATS 2019 Toward a Characterization of Loss Functions for Distribution Learning NeurIPS 2019 Towards Clustering High-dimensional Gaussian Mixture Clouds in Linear Running Time AISTATS 2019 Training Complex Models with Multi-Task Weak Supervision AAAI 2019 Transductive Bounds for the Multi-Class Majority Vote Classifier AAAI 2019 Transferability and Hardness of Supervised Classification Tasks ICCV 2019 Transforming Underwriting in the Life Insurance Industry AAAI 2019 Uncovering Probabilistic Implications in Typological Knowledge Bases ACL 2019 Unified Sample-Optimal Property Estimation in Near-Linear Time NeurIPS 2019 Uniform concentration and symmetrization for weak interactions COLT 2019 Uniform convergence may be unable to explain generalization in deep learning NeurIPS 2019 Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension ICML 2019 Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit AISTATS 2019 Universality in Learning from Linear Measurements NeurIPS 2019 Unsupervised Primitive Discovery for Improved 3D Generative Modeling CVPR 2019 Variance-based Regularization with Convex Objectives JMLR 2019 Variance of Average Surprisal: A Better Predictor for Quality of Grammar from Unsupervised PCFG Induction ACL 2019