Overparameterized Linear Regression under Adversarial Attacks

13 April 2022

Papers citing "Overparameterized Linear Regression under Adversarial Attacks"

15 / 15 papers shown

Title
Risk Analysis and Design Against Adversarial Actions M. Campi A. Carè Luis G. Crespo S. Garatti Federico A. Ramponi AAML 150 0 0 02 May 2025
Analysis of the vulnerability of machine learning regression models to adversarial attacks using data from 5G wireless networks Leonid Legashev A. Zhigalov Denis Parfenov AAML 36 0 0 01 May 2025
Efficient Optimization Algorithms for Linear Adversarial Training Antônio H. Ribeiro Thomas B. Schon Dave Zahariah Francis Bach AAML 45 1 0 16 Oct 2024
An integrated perspective of robustness in regression through the lens of the bias-variance trade-off Akifumi Okuno 19 0 0 15 Jul 2024
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis Zhang Chen Luca Demetrio Srishti Gupta Xiaoyi Feng Zhaoqiang Xia ... Maura Pintor Luca Oneto Ambra Demontis Battista Biggio Fabio Roli AAML 36 1 0 14 Jun 2024
$H$ -Consistency Guarantees for Regression Anqi Mao M. Mohri Yutao Zhong 33 9 0 28 Mar 2024
$Asymptotic Behavior of Adversarial Training Estimator under $\ell_\infty$-Perturbation$ Asymptotic Behavior of Adversarial Training Estimator under $\ell_\infty$ -Perturbation Yiling Xie Xiaoming Huo 36 2 0 27 Jan 2024
Dense Hopfield Networks in the Teacher-Student Setting Robin Thériault Daniele Tantari AAML 38 3 0 08 Jan 2024
Regularization properties of adversarially-trained linear regression Antônio H. Ribeiro Dave Zachariah Francis Bach Thomas B. Schon AAML 36 8 0 16 Oct 2023
Sup-Norm Convergence of Deep Neural Network Estimator for Nonparametric Regression by Adversarial Training Masaaki Imaizumi AAML 16 4 0 08 Jul 2023
Robust Nonparametric Regression under Poisoning Attack Puning Zhao Z. Wan AAML 28 8 0 26 May 2023
On the ISS Property of the Gradient Flow for Single Hidden-Layer Neural Networks with Linear Activations A. C. B. D. Oliveira Milad Siami Eduardo Sontag 19 2 0 17 May 2023
Deep networks for system identification: a Survey G. Pillonetto Aleksandr Aravkin Daniel Gedon L. Ljung Antônio H. Ribeiro Thomas B. Schon OOD 37 36 0 30 Jan 2023
Surprises in adversarially-trained linear regression Antônio H. Ribeiro Dave Zachariah Thomas B. Schon AAML 110 2 0 25 May 2022
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 186 275 0 28 Sep 2021