mean estimation

All-Purpose Mean Estimation over R AAAI 2026 A Quasi-Polynomial Time Mean Estimator Under Mean-Shift Contamination with Unknown Covariance COLT 2026 Explore, Refine, then Commit: Nearly Optimal Multi-Group Mean Estimation with Active Learning UAI 2026 High-Dimensional Gaussian Mean Estimation under Realizable Contamination COLT 2026 Linear Regression with Heteroskedastic Errors UAI 2026 Open Problem: Is Interaction Necessary for Order-Optimal 1-bit Mean Estimation? COLT 2026 Uniform Convergence Beyond Glivenko-Cantelli ALT 2026 Distribution-Aware Mean Estimation under User-level Local Differential Privacy AISTATS 2025 Gaussian Graphical Modelling Without Independence Assumptions for Uncentered Data AAAI 2025 Heavy-tailed Estimation is Easier than Adversarial Contamination COLT 2025 Learning High-dimensional Gaussians from Censored Data AISTATS 2025 Open Problem: Data Selection for Regression Tasks COLT 2025 Scalable Decentralized Algorithms for Online Personalized Mean Estimation AAAI 2025 A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy NeurIPS 2024 Automatic Outlier Rectification via Optimal Transport NeurIPS 2024 Differentially Private Optimization with Sparse Gradients NeurIPS 2024 Dimension-free Private Mean Estimation for Anisotropic Distributions NeurIPS 2024 Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract COLT 2024 Locally Private and Robust Multi-Armed Bandits NeurIPS 2024 Mean Estimation in the Add-Remove Model of Differential Privacy ICML 2024 Optimal Differentially Private Model Training with Public Data ICML 2024 Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages ICML 2024 Provable Mutual Benefits from Federated Learning in Privacy-Sensitive Domains AISTATS 2024 Robust Mixture Learning when Outliers Overwhelm Small Groups NeurIPS 2024 Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination ICML 2024