Robustly Learning a Gaussian: Getting Optimal Error, Efficiently

12 April 2017

Papers citing "Robustly Learning a Gaussian: Getting Optimal Error, Efficiently"

38 / 38 papers shown

Title
Learning High-dimensional Gaussians from Censored Data Arnab Bhattacharyya C. Daskalakis Themis Gouleakis Yuhao Wang 31 0 0 28 Apr 2025
Improved Robust Estimation for Erdős-Rényi Graphs: The Sparse Regime and Optimal Breakdown Point Hongjie Chen Jingqiu Ding Yiding Hua Stefan Tiegel 66 0 0 05 Mar 2025
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination Ilias Diakonikolas Giannis Iakovidis D. Kane Thanasis Pittas 87 0 0 20 Feb 2025
Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination Ilias Diakonikolas Daniel M. Kane Sushrut Karmalkar Ankit Pensia Thanasis Pittas 34 0 0 15 Mar 2024
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption Shubhada Agrawal Timothée Mathieu D. Basu Odalric-Ambrym Maillard 30 2 0 28 Sep 2023
Efficient List-Decodable Regression using Batches Abhimanyu Das Ayush Jain Weihao Kong Rajat Sen 28 4 0 23 Nov 2022
Outlier Robust and Sparse Estimation of Linear Regression Coefficients Takeyuki Sasai Hironori Fujisawa 35 4 0 24 Aug 2022
Robust and Sparse Estimation of Linear Regression Coefficients with Heavy-tailed Noises and Covariates Takeyuki Sasai 26 4 0 15 Jun 2022
Robust estimation algorithms don't need to know the corruption level Ayush Jain A. Orlitsky V. Ravindrakumar 21 6 0 11 Feb 2022
Private Robust Estimation by Stabilizing Convex Relaxations Pravesh Kothari Pasin Manurangsi A. Velingker 38 46 0 07 Dec 2021
Kalman Filtering with Adversarial Corruptions Sitan Chen Frederic Koehler Ankur Moitra Morris Yau AAML 27 10 0 11 Nov 2021
Robust Estimation for Random Graphs Jayadev Acharya Ayush Jain Gautam Kamath A. Suresh Huanyu Zhang 32 8 0 09 Nov 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation Gavin Brown Marco Gaboardi Adam D. Smith Jonathan R. Ullman Lydia Zakynthinou FedML 28 48 0 24 Jun 2021
Learning GMMs with Nearly Optimal Robustness Guarantees Allen Liu Ankur Moitra 26 15 0 19 Apr 2021
SoS Degree Reduction with Applications to Clustering and Robust Moment Estimation David Steurer Stefan Tiegel 29 10 0 05 Jan 2021
Near-Optimal Statistical Query Hardness of Learning Halfspaces with Massart Noise Ilias Diakonikolas D. Kane 26 24 0 17 Dec 2020
Optimal Mean Estimation without a Variance Yeshwanth Cherapanamjeri Nilesh Tripuraneni Peter L. Bartlett Michael I. Jordan 26 21 0 24 Nov 2020
Optimal Robust Linear Regression in Nearly Linear Time Yeshwanth Cherapanamjeri Efe Aras Nilesh Tripuraneni Michael I. Jordan Nicolas Flammarion Peter L. Bartlett 35 35 0 16 Jul 2020
Learning Entangled Single-Sample Gaussians in the Subset-of-Signals Model Yingyu Liang Hui Yuan 23 5 0 10 Jul 2020
Estimating Principal Components under Adversarial Perturbations Pranjal Awasthi Xue Chen Aravindan Vijayaraghavan AAML 17 2 0 31 May 2020
Reducibility and Statistical-Computational Gaps from Secret Leakage Matthew Brennan Guy Bresler 38 86 0 16 May 2020
Robustly Learning any Clusterable Mixture of Gaussians Ilias Diakonikolas Samuel B. Hopkins D. Kane Sushrut Karmalkar 38 45 0 13 May 2020
Outlier-Robust Clustering of Non-Spherical Mixtures Ainesh Bakshi Pravesh Kothari 27 31 0 06 May 2020
Robust estimation with Lasso when outputs are adversarially contaminated Takeyuki Sasai Hironori Fujisawa 27 8 0 13 Apr 2020
All-In-One Robust Estimator of the Gaussian Mean A. Dalalyan A. Minasyan 30 25 0 04 Feb 2020
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering Ilias Diakonikolas Sushrut Karmalkar D. Kane Eric Price Alistair Stewart 23 41 0 19 Nov 2019
Distribution-Independent PAC Learning of Halfspaces with Massart Noise Ilias Diakonikolas Themis Gouleakis Christos Tzamos 46 80 0 24 Jun 2019
Robust subgaussian estimation of a mean vector in nearly linear time Jules Depersin Guillaume Lecué 21 92 0 07 Jun 2019
List-Decodable Linear Regression Sushrut Karmalkar Adam R. Klivans Pravesh Kothari 34 74 0 14 May 2019
$Outlier-robust estimation of a sparse linear model using $\ell_1$-penalized Huber's $M$-estimator$ Outlier-robust estimation of a sparse linear model using $\ell_1$ -penalized Huber's $M$ -estimator A. Dalalyan Philip Thompson 23 67 0 12 Apr 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 22 144 0 15 Jan 2019
Efficient Statistics, in High Dimensions, from Truncated Samples C. Daskalakis Themis Gouleakis Christos Tzamos Manolis Zampetakis 44 47 0 11 Sep 2018
Efficient Algorithms and Lower Bounds for Robust Linear Regression Ilias Diakonikolas Weihao Kong Alistair Stewart 27 161 0 31 May 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 72 149 0 01 May 2018
Learning Geometric Concepts with Nasty Noise Ilias Diakonikolas D. Kane Alistair Stewart AAML 37 85 0 05 Jul 2017
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers Jacob Steinhardt Moses Charikar Gregory Valiant 39 138 0 15 Mar 2017
Being Robust (in High Dimensions) Can Be Practical Ilias Diakonikolas Gautam Kamath D. Kane Jerry Li Ankur Moitra Alistair Stewart 19 252 0 02 Mar 2017
Robust Learning of Fixed-Structure Bayesian Networks Yu Cheng Ilias Diakonikolas D. Kane Alistair Stewart OOD 46 46 0 23 Jun 2016