Being Robust (in High Dimensions) Can Be Practical

2 March 2017

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

27 / 177 papers shown

Title
Spectral Signatures in Backdoor Attacks Brandon Tran Jerry Li Aleksander Madry AAML 24 775 0 01 Nov 2018
Robust Estimation and Generative Adversarial Nets Chao Gao Jiyi Liu Yuan Yao Weizhi Zhu 30 28 0 04 Oct 2018
Can Adversarially Robust Learning Leverage Computational Hardness? Saeed Mahloujifar Mohammad Mahmoody AAML OOD 19 48 0 02 Oct 2018
Estimating minimum effect with outlier selection Alexandra Carpentier S. Delattre Étienne Roquain Nicolas Verzélen 23 9 0 21 Sep 2018
Efficient Statistics, in High Dimensions, from Truncated Samples C. Daskalakis Themis Gouleakis Christos Tzamos Manolis Zampetakis 44 47 0 11 Sep 2018
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure Saeed Mahloujifar Dimitrios I. Diochnos Mohammad Mahmoody 25 150 0 09 Sep 2018
Robust classification via MOM minimization Guillaume Lecué M. Lerasle Timlothée Mathieu 16 47 0 09 Aug 2018
Robust Inference Under Heteroskedasticity via the Hadamard Estimator Yan Sun Weijie J. Su Yachong Yang Zhixiang Zhang 11 7 0 01 Jul 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
On the adversarial robustness of robust estimators Lifeng Lai Erhan Bayraktar 19 10 0 11 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 14 71 0 29 May 2018
Do Outliers Ruin Collaboration? Mingda Qiao 14 15 0 12 May 2018
Privately Learning High-Dimensional Distributions Gautam Kamath Jerry Li Vikrant Singhal Jonathan R. Ullman FedML 72 149 0 01 May 2018
Securing Distributed Gradient Descent in High Dimensional Statistical Learning Lili Su Jiaming Xu FedML 137 35 0 26 Apr 2018
Sever: A Robust Meta-Algorithm for Stochastic Optimization Ilias Diakonikolas Gautam Kamath D. Kane Jerry Li Jacob Steinhardt Alistair Stewart 23 288 0 07 Mar 2018
An Overview of Robust Subspace Recovery Gilad Lerman Tyler Maunu 28 130 0 02 Mar 2018
Robust Estimation via Robust Gradient Estimation Adarsh Prasad A. Suggala Sivaraman Balakrishnan Pradeep Ravikumar 30 220 0 19 Feb 2018
Outlier-robust moment-estimation via sum-of-squares Pravesh Kothari David Steurer 22 64 0 30 Nov 2017
Learning Discrete Distributions from Untrusted Batches Mingda Qiao Gregory Valiant FedML 33 34 0 22 Nov 2017
List-Decodable Robust Mean Estimation and Learning Mixtures of Spherical Gaussians Ilias Diakonikolas D. Kane Alistair Stewart 22 146 0 20 Nov 2017
Learning Geometric Concepts with Nasty Noise Ilias Diakonikolas D. Kane Alistair Stewart AAML 37 85 0 05 Jul 2017
Robustly Learning a Gaussian: Getting Optimal Error, Efficiently Ilias Diakonikolas Gautam Kamath D. Kane Jerry Li Ankur Moitra Alistair Stewart 27 135 0 12 Apr 2017
Resilience: A Criterion for Learning in the Presence of Arbitrary Outliers Jacob Steinhardt Moses Charikar Gregory Valiant 39 138 0 15 Mar 2017
Statistical Query Lower Bounds for Robust Estimation of High-dimensional Gaussians and Gaussian Mixtures Ilias Diakonikolas D. Kane Alistair Stewart 22 230 0 10 Nov 2016
Robust Learning of Fixed-Structure Bayesian Networks Yu Cheng Ilias Diakonikolas D. Kane Alistair Stewart OOD 46 46 0 23 Jun 2016
Robust Estimators in High Dimensions without the Computational Intractability Ilias Diakonikolas Gautam Kamath D. Kane Jingkai Li Ankur Moitra Alistair Stewart 21 505 0 21 Apr 2016