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On Tail Decay Rate Estimation of Loss Function Distributions JMLR 2024 On the Adversarial Robustness of Benjamini Hochberg NeurIPS 2024 On the Misspecification of Linear Assumptions in Synthetic Controls AISTATS 2024 Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift NeurIPS 2024 Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime NeurIPS 2024 Partial identification of the maximum mean discrepancy with mismeasured data UAI 2024 Piecewise deterministic generative models NeurIPS 2024 Post-Regularization Confidence Bands for Ordinary Differential Equations JMLR 2024 Power of knockoff: The impact of ranking algorithm, augmented design, and symmetric statistic JMLR 2024 Precise Model Benchmarking with Only a Few Observations EMNLP 2024 Preference-based Pure Exploration NeurIPS 2024 Public-data Assisted Private Stochastic Optimization: Power and Limitations NeurIPS 2024 Rejection via Learning Density Ratios NeurIPS 2024 Reliable Learning of Halfspaces under Gaussian Marginals NeurIPS 2024 Risk Measures and Upper Probabilities: Coherence and Stratification JMLR 2024 Robust group and simultaneous inferences for high-dimensional single index model NeurIPS 2024 Robust Sparse Regression with Non-Isotropic Designs NeurIPS 2024 ROME: Robust Multi-Modal Density Estimator IJCAI 2024 Semi-supervised Inference for Block-wise Missing Data without Imputation JMLR 2024 Simulation-Based Stacking AISTATS 2024 Sparse Recovery With Multiple Data Streams: An Adaptive Sequential Testing Approach JMLR 2024 Sparsistency for inverse optimal transport ICLR 2024 Spectral Learning of Shared Dynamics Between Generalized-Linear Processes NeurIPS 2024 Split Conformal Prediction and Non-Exchangeable Data JMLR 2024 Statistical and Causal Robustness for Causal Null Hypothesis Tests UAI 2024