Being Robust (in High Dimensions) Can Be Practical

2 March 2017

Papers citing "Being Robust (in High Dimensions) Can Be Practical"

50 / 177 papers shown

Title
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning Chuan Ma Jun Li Kang Wei Bo Liu Ming Ding Long Yuan Zhu Han H. Vincent Poor 64 43 0 18 Feb 2022
Robust estimation algorithms don't need to know the corruption level Ayush Jain A. Orlitsky V. Ravindrakumar 21 6 0 11 Feb 2022
Robust Estimation for Nonparametric Families via Generative Adversarial Networks Banghua Zhu Jiantao Jiao Michael I. Jordan GAN 31 4 0 02 Feb 2022
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms Jeongyeol Kwon Yonathan Efroni Constantine Caramanis Shie Mannor AAML 47 6 0 30 Jan 2022
On robustness and local differential privacy Mengchu Li Thomas B. Berrett Yi Yu 37 25 0 03 Jan 2022
Faster Algorithms and Constant Lower Bounds for the Worst-Case Expected Error Jonah Brown-Cohen 13 0 0 27 Dec 2021
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 35 8 0 09 Nov 2021
Robust Generalized Method of Moments: A Finite Sample Viewpoint Dhruv Rohatgi Vasilis Syrgkanis 18 2 0 06 Oct 2021
Outlier-Robust Sparse Estimation via Non-Convex Optimization Yu Cheng Ilias Diakonikolas Rong Ge Shivam Gupta D. Kane Mahdi Soltanolkotabi 49 13 0 23 Sep 2021
Heavy-tailed Streaming Statistical Estimation Che-Ping Tsai Adarsh Prasad Sivaraman Balakrishnan Pradeep Ravikumar 30 10 0 25 Aug 2021
Efficient Algorithms for Learning from Coarse Labels Dimitris Fotakis Alkis Kalavasis Vasilis Kontonis Christos Tzamos 23 15 0 22 Aug 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
Robust Regression Revisited: Acceleration and Improved Estimation Rates A. Jambulapati Jingkai Li T. Schramm Kevin Tian AAML 32 17 0 22 Jun 2021
Statistical Query Lower Bounds for List-Decodable Linear Regression Ilias Diakonikolas D. Kane Ankit Pensia Thanasis Pittas Alistair Stewart 21 21 0 17 Jun 2021
Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation Ilias Diakonikolas D. Kane Daniel Kongsgaard Jingkai Li Kevin Tian FedML 31 21 0 16 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 29 10 0 21 May 2021
Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time Yu Cheng Honghao Lin OOD 29 0 0 12 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
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 58 75 0 18 Feb 2021
Robust Policy Gradient against Strong Data Corruption Xuezhou Zhang Yiding Chen Xiaojin Zhu Wen Sun AAML 42 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
Optimal robust mean and location estimation via convex programs with respect to any pseudo-norms Jules Depersin Guillaume Lecué 20 12 0 01 Feb 2021
On the robustness to adversarial corruption and to heavy-tailed data of the Stahel-Donoho median of means Jules Depersin Guillaume Lecué 35 12 0 22 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 Aleksander Madry Bo Li Tom Goldstein SILM 34 271 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
Robustly Learning Mixtures of $k$ Arbitrary Gaussians Ainesh Bakshi Ilias Diakonikolas Hengrui Jia D. Kane Pravesh Kothari Santosh Vempala 26 64 0 03 Dec 2020
On the Error Resistance of Hinge Loss Minimization Kunal Talwar 24 4 0 02 Dec 2020
Optimal Mean Estimation without a Variance Yeshwanth Cherapanamjeri Nilesh Tripuraneni Peter L. Bartlett Michael I. Jordan 26 21 0 24 Nov 2020
List-Decodable Mean Estimation in Nearly-PCA Time Ilias Diakonikolas D. Kane Daniel Kongsgaard Jingkai Li Kevin Tian 21 17 0 19 Nov 2020
Settling the Robust Learnability of Mixtures of Gaussians Allen Liu Ankur Moitra 40 41 0 06 Nov 2020
Reliable Graph Neural Networks via Robust Aggregation Simon Geisler Daniel Zügner Stephan Günnemann AAML OOD 14 71 0 29 Oct 2020
Adversarial Robust Low Rank Matrix Estimation: Compressed Sensing and Matrix Completion Takeyuki Sasai Hironori Fujisawa 25 0 0 25 Oct 2020
Computationally and Statistically Efficient Truncated Regression C. Daskalakis Themis Gouleakis Christos Tzamos Manolis Zampetakis 22 29 0 22 Oct 2020
Online and Distribution-Free Robustness: Regression and Contextual Bandits with Huber Contamination Sitan Chen Frederic Koehler Ankur Moitra Morris Yau 26 34 0 08 Oct 2020
A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise Ilias Diakonikolas D. Kane Vasilis Kontonis Christos Tzamos Nikos Zarifis 13 20 0 04 Oct 2020
$Robust Mean Estimation in High Dimensions via $\ell_0$ Minimization$ Robust Mean Estimation in High Dimensions via $\ell_0$ Minimization Jing Liu Aditya Deshmukh V. Veeravalli 14 0 0 21 Aug 2020
Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers Lunjia Hu Omer Reingold OOD 31 5 0 18 Aug 2020
A Functional Perspective on Learning Symmetric Functions with Neural Networks Aaron Zweig Joan Bruna 14 21 0 16 Aug 2020
Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization Samuel B. Hopkins Jingkai Li Fred Zhang OOD 6 62 0 31 Jul 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
Learning Entangled Single-Sample Gaussians in the Subset-of-Signals Model Yingyu Liang Hui Yuan 23 5 0 10 Jul 2020
Efficient Parameter Estimation of Truncated Boolean Product Distributions Dimitris Fotakis Alkis Kalavasis Christos Tzamos TPM 19 13 0 05 Jul 2020
Online Robust Regression via SGD on the l1 loss Scott Pesme Nicolas Flammarion FedML 21 32 0 01 Jul 2020
Robust Linear Regression: Optimal Rates in Polynomial Time Ainesh Bakshi Adarsh Prasad 24 58 0 29 Jun 2020