multiple testing

From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms ICML 2025 Conformalized Multiple Testing after Data-dependent Selection NeurIPS 2024 DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data AISTATS 2024 False discovery proportion envelopes with m-consistency JMLR 2024 Foundations of Testing for Finite-Sample Causal Discovery ICML 2024 On the Adversarial Robustness of Benjamini Hochberg NeurIPS 2024 Robust group and simultaneous inferences for high-dimensional single index model NeurIPS 2024 Sparse Recovery With Multiple Data Streams: An Adaptive Sequential Testing Approach JMLR 2024 Adaptive False Discovery Rate Control with Privacy Guarantee JMLR 2023 AMDP: An Adaptive Detection Procedure for False Discovery Rate Control in High-Dimensional Mediation Analysis NeurIPS 2023 DART: Distance Assisted Recursive Testing JMLR 2023 Principled Out-of-Distribution Detection via Multiple Testing JMLR 2023 Selection by Prediction with Conformal p-values JMLR 2023 Calibrated Nonparametric Scan Statistics for Anomalous Pattern Detection in Graphs AAAI 2022 Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach JMLR 2022 Online Control of the False Discovery Rate under "Decision Deadlines" AISTATS 2022 Estimating the Number and Effect Sizes of Non-null Hypotheses ICML 2020 Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits ICML 2019 Finding Statistically Significant Interactions between Continuous Features IJCAI 2019 A Bandit Approach to Sequential Experimental Design with False Discovery Control NeurIPS 2018 SAFFRON: an Adaptive Algorithm for Online Control of the False Discovery Rate ICML 2018 Online control of the false discovery rate with decaying memory NeurIPS 2017 Power of Ordered Hypothesis Testing ICML 2016 Multiple Testing under Dependence via Semiparametric Graphical Models ICML 2014