Agnostic Estimation of Mean and Covariance

24 April 2016

Papers citing "Agnostic Estimation of Mean and Covariance"

50 / 101 papers shown

Title
SoS Degree Reduction with Applications to Clustering and Robust Moment Estimation David Steurer Stefan Tiegel 29 10 0 05 Jan 2021
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses Micah Goldblum Dimitris Tsipras Chulin Xie Xinyun Chen Avi Schwarzschild D. Song A. Madry Bo-wen Li Tom Goldstein SILM 32 271 0 18 Dec 2020
Learning from History for Byzantine Robust Optimization Sai Praneeth Karimireddy Lie He Martin Jaggi FedML AAML 30 174 0 18 Dec 2020
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
Settling the Robust Learnability of Mixtures of Gaussians Allen Liu Ankur Moitra 40 41 0 06 Nov 2020
Outlier Robust Mean Estimation with Subgaussian Rates via Stability Ilias Diakonikolas D. Kane Ankit Pensia 29 57 0 30 Jul 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
Subspace approximation with outliers Amit Deshpande Rameshwar Pratap 27 3 0 30 Jun 2020
Generalization Bounds in the Presence of Outliers: a Median-of-Means Study Pierre Laforgue Guillaume Staerman Stéphan Clémençon 13 3 0 09 Jun 2020
Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability Sitan Chen Frederic Koehler Ankur Moitra Morris Yau 26 21 0 08 Jun 2020
Designing Differentially Private Estimators in High Dimensions Aditya Dhar Jason Huang 24 1 0 02 Jun 2020
Universal Robust Regression via Maximum Mean Discrepancy Pierre Alquier Mathieu Gerber 38 15 0 01 Jun 2020
Estimating Principal Components under Adversarial Perturbations Pranjal Awasthi Xue Chen Aravindan Vijayaraghavan AAML 17 2 0 31 May 2020
Robust estimation via generalized quasi-gradients Banghua Zhu Jiantao Jiao Jacob Steinhardt 23 43 0 28 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
High-Dimensional Robust Mean Estimation via Gradient Descent Yu Cheng Ilias Diakonikolas Rong Ge Mahdi Soltanolkotabi 17 31 0 04 May 2020
Robust estimation with Lasso when outputs are adversarially contaminated Takeyuki Sasai Hironori Fujisawa 27 8 0 13 Apr 2020
On Robust Mean Estimation under Coordinate-level Corruption Zifan Liu Jongho Park Theodoros Rekatsinas Christos Tzamos 33 8 0 10 Feb 2020
All-In-One Robust Estimator of the Gaussian Mean A. Dalalyan A. Minasyan 30 25 0 04 Feb 2020
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer Hong Chang Virat Shejwalkar Reza Shokri Amir Houmansadr FedML 26 167 0 24 Dec 2019
Optimal Robust Learning of Discrete Distributions from Batches Ayush Jain A. Orlitsky 16 14 0 19 Nov 2019
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
A Fast Spectral Algorithm for Mean Estimation with Sub-Gaussian Rates Zhixian Lei K. Luh Prayaag Venkat Fred Zhang 66 34 0 13 Aug 2019
Estimating location parameters in entangled single-sample distributions Ankit Pensia Varun Jog Po-Ling Loh 16 7 0 06 Jul 2019
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection Yihe Dong Samuel B. Hopkins Jungshian Li 21 99 0 26 Jun 2019
Distribution-Independent PAC Learning of Halfspaces with Massart Noise Ilias Diakonikolas Themis Gouleakis Christos Tzamos 46 80 0 24 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
Better Algorithms for Stochastic Bandits with Adversarial Corruptions Anupam Gupta Tomer Koren Kunal Talwar AAML 8 151 0 22 Feb 2019
High Dimensional Robust $M$ -Estimation: Arbitrary Corruption and Heavy Tails L. Liu Tianyang Li Constantine Caramanis 21 14 0 24 Jan 2019
Stronger Data Poisoning Attacks Break Data Sanitization Defenses Pang Wei Koh Jacob Steinhardt Percy Liang 6 240 0 02 Nov 2018
Mean Estimation with Sub-Gaussian Rates in Polynomial Time Samuel B. Hopkins 18 79 0 19 Sep 2018
Efficient Statistics, in High Dimensions, from Truncated Samples C. Daskalakis Themis Gouleakis Christos Tzamos Manolis Zampetakis 44 47 0 11 Sep 2018
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett FedML 32 98 0 14 Jun 2018
Efficient Algorithms and Lower Bounds for Robust Linear Regression Ilias Diakonikolas Weihao Kong Alistair Stewart 27 161 0 31 May 2018
High Dimensional Robust Sparse Regression L. Liu Yanyao Shen Tianyang Li Constantine Caramanis 12 71 0 29 May 2018
Robust Nonparametric Regression under Huber's $ε$ -contamination Model S. Du Yining Wang Sivaraman Balakrishnan Pradeep Ravikumar Aarti Singh 28 12 0 26 May 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 72 149 0 01 May 2018
Efficient Algorithms for Outlier-Robust Regression Adam R. Klivans Pravesh Kothari Raghu Meka AAML 24 154 0 08 Mar 2018
Robust Estimation via Robust Gradient Estimation Adarsh Prasad A. Suggala Sivaraman Balakrishnan Pradeep Ravikumar 30 220 0 19 Feb 2018
Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent Yudong Chen Lili Su Jiaming Xu FedML 19 241 0 16 May 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 21 252 0 02 Mar 2017
Robust Sparse Estimation Tasks in High Dimensions Jerry Li 53 27 0 20 Feb 2017
Robust Regression via Mutivariate Regression Depth Chao Gao 38 48 0 15 Feb 2017
Learning from Untrusted Data Moses Charikar Jacob Steinhardt Gregory Valiant FedML OOD 38 292 0 07 Nov 2016
Robust Learning of Fixed-Structure Bayesian Networks Yu Cheng Ilias Diakonikolas D. Kane Alistair Stewart OOD 46 46 0 23 Jun 2016