robust statistics

All-Purpose Mean Estimation over R AAAI 2026 A Quasi-Polynomial Time Mean Estimator Under Mean-Shift Contamination with Unknown Covariance COLT 2026 On the Robustness of Bandit Multiple Testing AAAI 2026 Harnessing Robust Statistics for Trustworthy AI AAAI 2025 Learning from biased positive-unlabeled data via threshold calibration AISTATS 2025 On the Robustness of Kernel Goodness-of-Fit Tests JMLR 2025 Outlier-Robust Linear System Identification Under Heavy-Tailed Noise L4DC 2025 A Subspace-Constrained Tyler's Estimator and its Applications to Structure from Motion CVPR 2024 Beyond Catoni: Sharper Rates for Heavy-Tailed and Robust Mean Estimation COLT 2024 Certified Adversarial Robustness via Randomized α-Smoothing for Regression Models NeurIPS 2024 Learning with a linear loss function: excess risk and estimation bounds for ERM, minmax MOM and their regularized versions with applications to robustness in sparse PCA. JMLR 2024 MAC Advice for facility location mechanism design NeurIPS 2024 Robust Non-linear Normalization of Heterogeneous Feature Distributions with Adaptive Tanh-Estimators AISTATS 2024 Robust Sparse Regression with Non-Isotropic Designs NeurIPS 2024 Robust SVD Made Easy: A fast and reliable algorithm for large-scale data analysis AISTATS 2024 Statistical Multicriteria Benchmarking via the GSD-Front NeurIPS 2024 Towards Robust Offline Reinforcement Learning under Diverse Data Corruption ICLR 2024 Adaptive Data Depth via Multi-Armed Bandits JMLR 2023 A Robust Test for the Stationarity Assumption in Sequential Decision Making ICML 2023 A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm NeurIPS 2023 Byzantine-Robust Federated Learning with Optimal Statistical Rates AISTATS 2023 Efficient List-Decodable Regression using Batches ICML 2023 From Robustness to Privacy and Back ICML 2023 Huber-robust confidence sequences AISTATS 2023 Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression NeurIPS 2023