false discovery rate

Power of knockoff: The impact of ranking algorithm, augmented design, and symmetric statistic JMLR 2024 Robust group and simultaneous inferences for high-dimensional single index model NeurIPS 2024 Selective Generation for Controllable Language Models NeurIPS 2024 Testing Semantic Importance via Betting NeurIPS 2024 Adaptive False Discovery Rate Control with Privacy Guarantee JMLR 2023 Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations NeurIPS 2023 AMDP: An Adaptive Detection Procedure for False Discovery Rate Control in High-Dimensional Mediation Analysis NeurIPS 2023 Certified Policy Smoothing for Cooperative Multi-Agent Reinforcement Learning AAAI 2023 DART: Distance Assisted Recursive Testing JMLR 2023 Delving into Noisy Label Detection with Clean Data ICML 2023 Derandomized novelty detection with FDR control via conformal e-values NeurIPS 2023 Facial Expression Recognition with Adaptive Frame Rate based on Multiple Testing Correction ICML 2023 False Discovery Proportion control for aggregated Knockoffs NeurIPS 2023 Group SLOPE Penalized Low-Rank Tensor Regression JMLR 2023 Statistically Significant Concept-based Explanation of Image Classifiers via Model Knockoffs IJCAI 2023 Stepdown SLOPE for Controlled Feature Selection AAAI 2023 AutoMS: Automatic Model Selection for Novelty Detection with Error Rate Control NeurIPS 2022 Efficient Causal Structure Learning from Multiple Interventional Datasets with Unknown Targets AAAI 2022 Error-Based Knockoffs Inference for Controlled Feature Selection AAAI 2022 Feature screening with kernel knockoffs AISTATS 2022 Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach JMLR 2022 Normalizing Flows for Knockoff-free Controlled Feature Selection NeurIPS 2022 Online Control of the False Discovery Rate under "Decision Deadlines" AISTATS 2022 Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies AISTATS 2022 Asynchronous Online Testing of Multiple Hypotheses JMLR 2021