Learning from Untrusted Data

7 November 2016

Papers citing "Learning from Untrusted Data"

50 / 186 papers shown

Title
Robust Estimation for Random Graphs Jayadev Acharya Ayush Jain Gautam Kamath A. Suresh Huanyu Zhang 30 8 0 09 Nov 2021
Byzantine Fault-Tolerance in Federated Local SGD under 2f-Redundancy Nirupam Gupta Thinh T. Doan Nitin H. Vaidya FedML 33 11 0 26 Aug 2021
Efficient Algorithms for Learning from Coarse Labels Dimitris Fotakis Alkis Kalavasis Vasilis Kontonis Christos Tzamos 23 15 0 22 Aug 2021
LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning Kamala Varma Yi Zhou Nathalie Baracaldo Ali Anwar FedML 31 16 0 26 Jul 2021
Robust Online Convex Optimization in the Presence of Outliers T. Erven Sarah Sachs Wouter M. Koolen W. Kotłowski 19 8 0 05 Jul 2021
Exponential Weights Algorithms for Selective Learning Mingda Qiao Gregory Valiant 14 1 0 29 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
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data Eugenia Iofinova Nikola Konstantinov Christoph H. Lampert FaML 36 0 0 22 Jun 2021
Statistical Query Lower Bounds for List-Decodable Linear Regression Ilias Diakonikolas D. Kane Ankit Pensia Thanasis Pittas Alistair Stewart 13 21 0 17 Jun 2021
A Survey on Fault-tolerance in Distributed Optimization and Machine Learning Shuo Liu AI4CE OOD 58 13 0 16 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
Semi-verified PAC Learning from the Crowd Shiwei Zeng Jie Shen 30 3 0 13 Jun 2021
Corruption-Robust Offline Reinforcement Learning Xuezhou Zhang Yiding Chen Jerry Zhu Wen Sun OffRL 38 39 0 11 Jun 2021
Sum of Ranked Range Loss for Supervised Learning Shu Hu Yiming Ying Xin Wang Siwei Lyu 31 23 0 07 Jun 2021
Privately Learning Mixtures of Axis-Aligned Gaussians Ishaq Aden-Ali H. Ashtiani Christopher Liaw FedML 35 12 0 03 Jun 2021
Learning a Latent Simplex in Input-Sparsity Time Ainesh Bakshi Chiranjib Bhattacharyya R. Kannan David P. Woodruff Samson Zhou 39 10 0 17 May 2021
Robust Learning of Fixed-Structure Bayesian Networks in Nearly-Linear Time Yu Cheng Honghao Lin OOD 29 0 0 12 May 2021
Learning GMMs with Nearly Optimal Robustness Guarantees Allen Liu Ankur Moitra 26 15 0 19 Apr 2021
Formal Verification of Stochastic Systems with ReLU Neural Network Controllers Shiqi Sun Yan Zhang Xusheng Luo Panagiotis Vlantis Miroslav Pajic Michael M. Zavlanos 11 5 0 08 Mar 2021
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 53 75 0 18 Feb 2021
Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification A. Rangi Long Tran-Thanh Haifeng Xu M. Franceschetti AAML 17 13 0 15 Feb 2021
Fairness-Aware PAC Learning from Corrupted Data Nikola Konstantinov Christoph H. Lampert 11 17 0 11 Feb 2021
Robust Policy Gradient against Strong Data Corruption Xuezhou Zhang Yiding Chen Xiaojin Zhu Wen Sun AAML 40 37 0 11 Feb 2021
Defense Against Reward Poisoning Attacks in Reinforcement Learning Kiarash Banihashem Adish Singla Goran Radanović AAML 37 26 0 10 Feb 2021
Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descent Nirupam Gupta Nitin H. Vaidya 15 15 0 28 Jan 2021
Approximate Byzantine Fault-Tolerance in Distributed Optimization Shuo Liu Nirupam Gupta Nitin H. Vaidya 33 42 0 22 Jan 2021
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
From Weakly Supervised Learning to Biquality Learning: an Introduction Pierre Nodet V. Lemaire A. Bondu Antoine Cornuéjols A. Ouorou 19 21 0 16 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 19 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 13 17 0 19 Nov 2020
Settling the Robust Learnability of Mixtures of Gaussians Allen Liu Ankur Moitra 40 41 0 06 Nov 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 14 29 0 22 Oct 2020
Importance Reweighting for Biquality Learning Pierre Nodet V. Lemaire A. Bondu Antoine Cornuéjols NoLa 27 6 0 19 Oct 2020
Online and Distribution-Free Robustness: Regression and Contextual Bandits with Huber Contamination Sitan Chen Frederic Koehler Ankur Moitra Morris Yau 18 34 0 08 Oct 2020
Towards Bidirectional Protection in Federated Learning Lun Wang Qi Pang Shuai Wang D. Song FedML 25 3 0 02 Oct 2020
Consistent regression when oblivious outliers overwhelm Tommaso dÓrsi Gleb Novikov David Steurer 12 15 0 30 Sep 2020
Byzantine Fault-Tolerance in Decentralized Optimization under Minimal Redundancy Nirupam Gupta Thinh T. Doan Nitin H. Vaidya 14 4 0 30 Sep 2020
Using satellite imagery to understand and promote sustainable development Marshall Burke Anne Driscoll David B. Lobell Stefano Ermon 14 312 0 23 Sep 2020
CLEANN: Accelerated Trojan Shield for Embedded Neural Networks Mojan Javaheripi Mohammad Samragh Gregory Fields T. Javidi F. Koushanfar AAML FedML 11 42 0 04 Sep 2020
Robust Mean Estimation on Highly Incomplete Data with Arbitrary Outliers Lunjia Hu Omer Reingold OOD 31 5 0 18 Aug 2020
Byzantine Fault-Tolerant Distributed Machine Learning Using Stochastic Gradient Descent (SGD) and Norm-Based Comparative Gradient Elimination (CGE) Nirupam Gupta Shuo Liu Nitin H. Vaidya FedML 24 11 0 11 Aug 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
Efficient Parameter Estimation of Truncated Boolean Product Distributions Dimitris Fotakis Alkis Kalavasis Christos Tzamos TPM 13 13 0 05 Jul 2020
Online Robust Regression via SGD on the l1 loss Scott Pesme Nicolas Flammarion FedML 18 32 0 01 Jul 2020
Robust Linear Regression: Optimal Rates in Polynomial Time Ainesh Bakshi Adarsh Prasad 24 58 0 29 Jun 2020
Byzantine-Resilient High-Dimensional Federated Learning Deepesh Data Suhas Diggavi FedML AAML 21 41 0 22 Jun 2020