Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers

15 March 2017

Papers citing "Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers"

24 / 24 papers shown

Title
Towards Trustworthy Federated Learning with Untrusted Participants Youssef Allouah R. Guerraoui John Stephan FedML 43 0 0 03 May 2025
Robust Sparse Mean Estimation via Incremental Learning Jianhao Ma Ruidi Chen Yinghui He S. Fattahi Wei Hu 30 0 0 24 May 2023
Robust Estimation under the Wasserstein Distance Sloan Nietert Rachel Cummings Ziv Goldfeld 28 4 0 02 Feb 2023
Near Optimal Private and Robust Linear Regression Xiyang Liu Prateek Jain Weihao Kong Sewoong Oh A. Suggala 26 9 0 30 Jan 2023
Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances Sloan Nietert Ritwik Sadhu Ziv Goldfeld Kengo Kato 22 36 0 17 Oct 2022
Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models Pranjal Awasthi Abhimanyu Das Weihao Kong Rajat Sen 17 5 0 09 Jun 2022
Communication-efficient distributed eigenspace estimation with arbitrary node failures Vasileios Charisopoulos Anil Damle 11 1 0 31 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 91 30 0 24 May 2022
Byzantine Fault Tolerance in Distributed Machine Learning : a Survey Djamila Bouhata Hamouma Moumen Moumen Hamouma Ahcène Bounceur AI4CE 23 7 0 05 May 2022
Robust estimation algorithms don't need to know the corruption level Ayush Jain A. Orlitsky V. Ravindrakumar 8 6 0 11 Feb 2022
Robust Estimation for Random Graphs Jayadev Acharya Ayush Jain Gautam Kamath A. Suresh Huanyu Zhang 24 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 8 16 0 22 Oct 2021
Robust Regression Revisited: Acceleration and Improved Estimation Rates A. Jambulapati J. Li T. Schramm Kevin Tian AAML 19 17 0 22 Jun 2021
Outlier-Robust Learning of Ising Models Under Dobrushin's Condition Ilias Diakonikolas D. Kane Alistair Stewart Yuxin Sun 22 15 0 03 Feb 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 169 355 0 07 Dec 2020
Outlier Robust Mean Estimation with Subgaussian Rates via Stability Ilias Diakonikolas D. Kane Ankit Pensia 6 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 33 35 0 16 Jul 2020
Robustly Learning any Clusterable Mixture of Gaussians Ilias Diakonikolas Samuel B. Hopkins D. Kane Sushrut Karmalkar 26 45 0 13 May 2020
Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees Richeng Jin Yufan Huang Xiaofan He H. Dai Tianfu Wu FedML 11 63 0 25 Feb 2020
List Decodable Subspace Recovery P. Raghavendra Morris Yau 28 25 0 07 Feb 2020
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering Ilias Diakonikolas Sushrut Karmalkar D. Kane Eric Price Alistair Stewart 14 41 0 19 Nov 2019
Efficient Statistics, in High Dimensions, from Truncated Samples C. Daskalakis Themis Gouleakis Christos Tzamos Manolis Zampetakis 28 46 0 11 Sep 2018
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin Yudong Chen K. Ramchandran Peter L. Bartlett FedML 11 97 0 14 Jun 2018
Robust Estimators in High Dimensions without the Computational Intractability Ilias Diakonikolas Gautam Kamath D. Kane J. Li Ankur Moitra Alistair Stewart 21 505 0 21 Apr 2016