Algorithms for Heavy-Tailed Statistics: Regression, Covariance Estimation, and Beyond

23 December 2019

Papers citing "Algorithms for Heavy-Tailed Statistics: Regression, Covariance Estimation, and Beyond"

12 / 12 papers shown

Title
A Novel Framework for Improving the Breakdown Point of Robust Regression Algorithms Zheyi Fan Szu Hui Ng Q. Hu 25 0 0 20 May 2023
Robust empirical risk minimization via Newton's method Eirini Ioannou Muni Sreenivas Pydi Po-Ling Loh 23 2 0 30 Jan 2023
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions Ilias Diakonikolas D. Kane Jasper C. H. Lee Ankit Pensia 17 12 0 29 Nov 2022
List-Decodable Covariance Estimation Misha Ivkov Pravesh Kothari 16 7 0 22 Jun 2022
Covariance Estimation: Optimal Dimension-free Guarantees for Adversarial Corruption and Heavy Tails Pedro Abdalla Nikita Zhivotovskiy 30 25 0 17 May 2022
A Complete Characterization of Linear Estimators for Offline Policy Evaluation Juan C. Perdomo A. Krishnamurthy Peter L. Bartlett Sham Kakade OffRL 27 3 0 08 Mar 2022
Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance of Gaussians Optimally Pravesh Kothari Peter Manohar Brian Hu Zhang 20 16 0 22 Oct 2021
Inferring Hidden Structures in Random Graphs Wasim Huleihel 19 7 0 05 Oct 2021
A spectral algorithm for robust regression with subgaussian rates Jules Depersin 23 14 0 12 Jul 2020
Designing Differentially Private Estimators in High Dimensions Aditya Dhar Jason Huang 14 1 0 02 Jun 2020
Robust subgaussian estimation with VC-dimension Jules Depersin 27 12 0 24 Apr 2020
A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates Zhixian Lei K. Luh Prayaag Venkat Fred Zhang 60 35 0 13 Aug 2019