distribution testing

A Distribution Testing Approach to Clustering Distributions COLT 2026 Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions COLT 2026 Better Private Distribution Testing by Leveraging Unverified Auxiliary Data COLT 2025 How to Verify Any (Reasonable) Distribution Property: Computationally Sound Argument Systems for Distributions ICLR 2025 On the Robustness of Kernel Goodness-of-Fit Tests JMLR 2025 Data Distribution Valuation NeurIPS 2024 Differentially Private Equivalence Testing for Continuous Distributions and Applications NeurIPS 2024 Entropy testing and its application to testing Bayesian networks NeurIPS 2024 Equivalence Testing: The Power of Bounded Adaptivity AISTATS 2024 New Lower Bounds for Testing Monotonicity and Log Concavity of Distributions COLT 2024 Open Problem: Tight Characterization of Instance-Optimal Identity Testing COLT 2024 Replicable Uniformity Testing NeurIPS 2024 Testing Generated Distributions in GANs to Penalize Mode Collapse AISTATS 2024 Testing Self-Reducible Samplers AAAI 2024 A High-dimensional Convergence Theorem for U-statistics with Applications to Kernel-based Testing COLT 2023 Complexity of High-Dimensional Identity Testing with Coordinate Conditional Sampling COLT 2023 Data Structures for Density Estimation ICML 2023 Identifying Selection Bias from Observational Data AAAI 2023 Tester-Learners for Halfspaces: Universal Algorithms NeurIPS 2023 Testing of Horn Samplers AISTATS 2023 Testing of Index-Invariant Properties in the Huge Object Model COLT 2023 Testing Tail Weight of a Distribution Via Hazard Rate ALT 2023 Nearly-Tight Bounds for Testing Histogram Distributions NeurIPS 2022 On Scalable Testing of Samplers NeurIPS 2022 Sharp Constants in Uniformity Testing via the Huber Statistic COLT 2022