The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure

9 September 2018

Papers citing "The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure"

35 / 35 papers shown

Title
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao Rene Vidal 28 8 0 28 Sep 2023
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms Elvis Dohmatob M. Scetbon AAML OOD 28 0 0 01 Aug 2023
It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness Peiyu Xiong Michael W. Tegegn Jaskeerat Singh Sarin Shubhraneel Pal Julia Rubin SILM AAML 37 8 0 17 Mar 2023
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker Sihui Dai Wen-Luan Ding A. Bhagoji Daniel Cullina Ben Y. Zhao Haitao Zheng Prateek Mittal AAML 37 2 0 21 Feb 2023
Backdoor Learning for NLP: Recent Advances, Challenges, and Future Research Directions Marwan Omar SILM AAML 37 20 0 14 Feb 2023
Linking convolutional kernel size to generalization bias in face analysis CNNs Hao Liang J. O. Caro Vikram Maheshri Ankit B. Patel Guha Balakrishnan CVBM CML 23 0 0 07 Feb 2023
Enhancing Quantum Adversarial Robustness by Randomized Encodings Weiyuan Gong D. Yuan Weikang Li D. Deng AAML 26 19 0 05 Dec 2022
When are Local Queries Useful for Robust Learning? Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell OOD 40 1 0 12 Oct 2022
Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks Pascale Gourdeau Varun Kanade Marta Z. Kwiatkowska J. Worrell AAML 21 5 0 12 May 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes Elvis Dohmatob A. Bietti AAML 39 13 0 22 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 34 13 0 26 Feb 2022
Image classifiers can not be made robust to small perturbations Zheng Dai David K Gifford VLM AAML 36 1 0 07 Dec 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective Adhyyan Narang Vidya Muthukumar A. Sahai SILM AAML 38 1 0 27 Sep 2021
Universal Adversarial Examples and Perturbations for Quantum Classifiers Weiyuan Gong D. Deng AAML 37 23 0 15 Feb 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
Adversarial Classification: Necessary conditions and geometric flows Nicolas García Trillos Ryan W. Murray AAML 37 19 0 21 Nov 2020
Adversarial Robust Training of Deep Learning MRI Reconstruction Models Francesco Calivá Kaiyang Cheng Rutwik Shah V. Pedoia OOD AAML MedIm 30 10 0 30 Oct 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 157 0 08 Sep 2020
Learning from Noisy Labels with Deep Neural Networks: A Survey Hwanjun Song Minseok Kim Dongmin Park Yooju Shin Jae-Gil Lee NoLa 24 964 0 16 Jul 2020
Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations Chaoning Zhang Philipp Benz Tooba Imtiaz In-So Kweon SSL AAML 22 118 0 13 Jul 2020
Host-Pathongen Co-evolution Inspired Algorithm Enables Robust GAN Training Andrei Kucharavy El-Mahdi El-Mhamdi R. Guerraoui GAN 24 1 0 22 May 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 39 148 0 20 May 2020
Certifying Joint Adversarial Robustness for Model Ensembles M. Jonas David Evans AAML 21 2 0 21 Apr 2020
Utilizing Network Properties to Detect Erroneous Inputs Matt Gorbett Nathaniel Blanchard AAML 23 6 0 28 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 38 64 0 11 Feb 2020
Label-Consistent Backdoor Attacks Alexander Turner Dimitris Tsipras A. Madry AAML 11 383 0 05 Dec 2019
Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets Yogesh Balaji Tom Goldstein Judy Hoffman AAML 134 103 0 17 Oct 2019
Quantitative Verification of Neural Networks And its Security Applications Teodora Baluta Shiqi Shen Shweta Shinde Kuldeep S. Meel P. Saxena AAML 24 104 0 25 Jun 2019
Lower Bounds for Adversarially Robust PAC Learning Dimitrios I. Diochnos Saeed Mahloujifar Mohammad Mahmoody AAML 27 26 0 13 Jun 2019
Adversarially Robust Learning Could Leverage Computational Hardness Sanjam Garg S. Jha Saeed Mahloujifar Mohammad Mahmoody AAML 23 24 0 28 May 2019
Adversarial Training and Robustness for Multiple Perturbations Florian Tramèr Dan Boneh AAML SILM 28 375 0 30 Apr 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 22 1,998 0 08 Feb 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 36 318 0 29 Jan 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 22 144 0 15 Jan 2019
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 65 230 0 25 May 2018