Agnostic Estimation of Mean and Covariance

24 April 2016

Papers citing "Agnostic Estimation of Mean and Covariance"

50 / 101 papers shown

Title
Learning High-dimensional Gaussians from Censored Data Arnab Bhattacharyya C. Daskalakis Themis Gouleakis Yuhao Wang 31 0 0 28 Apr 2025
Computing High-dimensional Confidence Sets for Arbitrary Distributions Chao Gao Liren Shan Vaidehi Srinivas Aravindan Vijayaraghavan 50 0 0 03 Apr 2025
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination Ilias Diakonikolas Giannis Iakovidis D. Kane Thanasis Pittas 84 0 0 20 Feb 2025
Entangled Mean Estimation in High-Dimensions Ilias Diakonikolas D. Kane Sihan Liu Thanasis Pittas 45 1 0 10 Jan 2025
Tolerant Algorithms for Learning with Arbitrary Covariate Shift Surbhi Goel Abhishek Shetty Konstantinos Stavropoulos Arsen Vasilyan OOD 34 2 0 04 Jun 2024
Near-Optimal Mean Estimation with Unknown, Heteroskedastic Variances Spencer Compton Gregory Valiant 25 2 0 05 Dec 2023
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers Puning Zhao Zhiguo Wan OOD FedML 47 4 0 25 Jul 2023
Robust Sparse Mean Estimation via Incremental Learning Jianhao Ma Ruidi Chen Yinghui He S. Fattahi Wei Hu 36 0 0 24 May 2023
Nearly-Linear Time and Streaming Algorithms for Outlier-Robust PCA Ilias Diakonikolas D. Kane Ankit Pensia Thanasis Pittas OOD 36 10 0 04 May 2023
On Private and Robust Bandits Yulian Wu Xingyu Zhou Youming Tao Di Wang 24 5 0 06 Feb 2023
Robust empirical risk minimization via Newton's method Eirini Ioannou Muni Sreenivas Pydi Po-Ling Loh 23 2 0 30 Jan 2023
Statistically Optimal Robust Mean and Covariance Estimation for Anisotropic Gaussians A. Minasyan Nikita Zhivotovskiy 34 9 0 21 Jan 2023
Private estimation algorithms for stochastic block models and mixture models Hongjie Chen Vincent Cohen-Addad Tommaso dÓrsi Alessandro Epasto Jacob Imola David Steurer Stefan Tiegel FedML 43 20 0 11 Jan 2023
Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions Ilias Diakonikolas D. Kane Jasper C. H. Lee Ankit Pensia 25 12 0 29 Nov 2022
Efficient List-Decodable Regression using Batches Abhimanyu Das Ayush Jain Weihao Kong Rajat Sen 28 4 0 23 Nov 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao Wang C. Yuan 29 3 0 11 Oct 2022
On Optimal Learning Under Targeted Data Poisoning Steve Hanneke Amin Karbasi Mohammad Mahmoody Idan Mehalel Shay Moran AAML FedML 36 7 0 06 Oct 2022
On the Impossible Safety of Large AI Models El-Mahdi El-Mhamdi Sadegh Farhadkhani R. Guerraoui Nirupam Gupta L. Hoang Rafael Pinot Sébastien Rouault John Stephan 37 31 0 30 Sep 2022
Outlier Robust and Sparse Estimation of Linear Regression Coefficients Takeyuki Sasai Hironori Fujisawa 35 4 0 24 Aug 2022
Minimax Rates for Robust Community Detection Allen Liu Ankur Moitra 22 13 0 25 Jul 2022
List-Decodable Covariance Estimation Misha Ivkov Pravesh Kothari 24 7 0 22 Jun 2022
Robust and Sparse Estimation of Linear Regression Coefficients with Heavy-tailed Noises and Covariates Takeyuki Sasai 26 4 0 15 Jun 2022
Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models Pranjal Awasthi Abhimanyu Das Weihao Kong Rajat Sen 25 6 0 09 Jun 2022
Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models Ilias Diakonikolas D. Kane Yuxin Sun 33 1 0 09 Jun 2022
Robust Sparse Mean Estimation via Sum of Squares Ilias Diakonikolas D. Kane Sushrut Karmalkar Ankit Pensia Thanasis Pittas 28 21 0 07 Jun 2022
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds A. Mitra Arman Adibi George J. Pappas Hamed Hassani 44 6 0 06 Jun 2022
Byzantine-Robust Online and Offline Distributed Reinforcement Learning Yiding Chen Xuezhou Zhang Kaipeng Zhang Mengdi Wang Xiaojin Zhu OffRL 26 16 0 01 Jun 2022
Secure Federated Clustering Songze Li Sizai Hou Baturalp Buyukates A. Avestimehr FedML 23 9 0 31 May 2022
List-Decodable Sparse Mean Estimation Shiwei Zeng Jie Shen 27 9 0 28 May 2022
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees Banghua Zhu Lun Wang Qi Pang Shuai Wang Jiantao Jiao D. Song Michael I. Jordan FedML 98 30 0 24 May 2022
Robust Testing in High-Dimensional Sparse Models Anand George C. Canonne 43 3 0 16 May 2022
Streaming Algorithms for High-Dimensional Robust Statistics Ilias Diakonikolas D. Kane Ankit Pensia Thanasis Pittas 24 21 0 26 Apr 2022
Indiscriminate Data Poisoning Attacks on Neural Networks Yiwei Lu Gautam Kamath Yaoliang Yu AAML 43 24 0 19 Apr 2022
Robust estimation algorithms don't need to know the corruption level Ayush Jain A. Orlitsky V. Ravindrakumar 21 6 0 11 Feb 2022
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation Wenxiao Wang Alexander Levine S. Feizi AAML 20 60 0 05 Feb 2022
Robust Voting Rules from Algorithmic Robust Statistics Allen Liu Ankur Moitra 26 4 0 13 Dec 2021
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 30 8 0 09 Nov 2021
Polynomial-Time Sum-of-Squares Can Robustly Estimate Mean and Covariance of Gaussians Optimally Pravesh Kothari Peter Manohar Brian Hu Zhang 25 16 0 22 Oct 2021
Outlier-Robust Sparse Estimation via Non-Convex Optimization Yu Cheng Ilias Diakonikolas Rong Ge Shivam Gupta D. Kane Mahdi Soltanolkotabi 47 13 0 23 Sep 2021
ReLU Regression with Massart Noise Ilias Diakonikolas Jongho Park Christos Tzamos 56 11 0 10 Sep 2021
Robust Regression Revisited: Acceleration and Improved Estimation Rates A. Jambulapati Jingkai Li T. Schramm Kevin Tian AAML 32 17 0 22 Jun 2021
DORO: Distributional and Outlier Robust Optimization Runtian Zhai Chen Dan J. Zico Kolter Pradeep Ravikumar 33 60 0 11 Jun 2021
Adversarially robust change point detection Mengchu Li Yi Yu AAML 27 10 0 21 May 2021
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics J. Hayase Weihao Kong Raghav Somani Sewoong Oh AAML 29 150 0 22 Apr 2021
Learning GMMs with Nearly Optimal Robustness Guarantees Allen Liu Ankur Moitra 26 15 0 19 Apr 2021
Remember What You Want to Forget: Algorithms for Machine Unlearning Ayush Sekhari Jayadev Acharya Gautam Kamath A. Suresh FedML MU 41 288 0 04 Mar 2021
Robust Policy Gradient against Strong Data Corruption Xuezhou Zhang Yiding Chen Xiaojin Zhu Wen Sun AAML 40 37 0 11 Feb 2021
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition Ilias Diakonikolas D. Kane Alistair Stewart Yuxin Sun 24 15 0 03 Feb 2021