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On the Sample Complexity of Adversarial Multi-Source PAC Learning

24 February 2020

Dan Alistarh

Papers citing "On the Sample Complexity of Adversarial Multi-Source PAC Learning"

22 / 22 papers shown

Title
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization Florian E. Dorner Nikola Konstantinov Georgi Pashaliev Martin Vechev FedML 94 7 0 25 May 2023
A General Method for Robust Learning from Batches Ayush Jain A. Orlitsky OOD 36 16 0 25 Feb 2020
Efficiently Learning Structured Distributions from Untrusted Batches Sitan Chen Jingkai Li Ankur Moitra OOD FedML 61 16 0 05 Nov 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 166 2,052 0 08 Feb 2019
Robust Learning from Untrusted Sources Nikola Konstantinov Christoph H. Lampert FedML OOD 63 72 0 29 Jan 2019
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 305 1,059 0 29 Nov 2018
Universal Multi-Party Poisoning Attacks Saeed Mahloujifar Mohammad Mahmoody Ameer Mohammed AAML 57 46 0 10 Sep 2018
Mitigating Sybils in Federated Learning Poisoning Clement Fung Chris J. M. Yoon Ivan Beschastnikh AAML 58 507 0 14 Aug 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 192 2,063 0 10 Jul 2018
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett FedML 83 100 0 14 Jun 2018
Do Outliers Ruin Collaboration? Mingda Qiao 44 15 0 12 May 2018
Byzantine Stochastic Gradient Descent Dan Alistarh Zeyuan Allen-Zhu Jingkai Li FedML 73 297 0 23 Mar 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 127 1,517 0 05 Mar 2018
Certified Defenses against Adversarial Examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 115 969 0 29 Jan 2018
Learning Discrete Distributions from Untrusted Batches Mingda Qiao Gregory Valiant FedML 66 34 0 22 Nov 2017
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks Shiyu Liang Yixuan Li R. Srikant UQCV OODD 171 2,082 0 08 Jun 2017
On Fundamental Limits of Robust Learning Jiashi Feng 24 2 0 30 Mar 2017
Efficient PAC Learning from the Crowd Pranjal Awasthi Avrim Blum Nika Haghtalab Yishay Mansour FedML 44 20 0 21 Mar 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 171 3,480 0 07 Oct 2016
Robust Estimators in High Dimensions without the Computational Intractability Ilias Diakonikolas Gautam Kamath D. Kane Jingkai Li Ankur Moitra Alistair Stewart 73 513 0 21 Apr 2016
Distributed Robust Learning Jiashi Feng Huan Xu Shie Mannor OOD 90 53 0 21 Sep 2014
New Analysis and Algorithm for Learning with Drifting Distributions M. Mohri Andrés Munoz Medina 148 125 0 19 May 2012