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Overparameterized Linear Regression under Adversarial Attacks

Overparameterized Linear Regression under Adversarial Attacks

13 April 2022
Antônio H. Ribeiro
Thomas B. Schon
    AAML
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Papers citing "Overparameterized Linear Regression under Adversarial Attacks"

15 / 15 papers shown
Title
Risk Analysis and Design Against Adversarial Actions
Risk Analysis and Design Against Adversarial Actions
M. Campi
A. Carè
Luis G. Crespo
S. Garatti
Federico A. Ramponi
AAML
132
0
0
02 May 2025
Analysis of the vulnerability of machine learning regression models to adversarial attacks using data from 5G wireless networks
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
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
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
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
HHH-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 ℓ∞\ell_\inftyℓ∞​-Perturbation
Yiling Xie
Xiaoming Huo
36
2
0
27 Jan 2024
Dense Hopfield Networks in the Teacher-Student Setting
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
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
Sup-Norm Convergence of Deep Neural Network Estimator for Nonparametric Regression by Adversarial Training
Masaaki Imaizumi
AAML
13
4
0
08 Jul 2023
Robust Nonparametric Regression under Poisoning Attack
Robust Nonparametric Regression under Poisoning Attack
Puning Zhao
Z. Wan
AAML
26
8
0
26 May 2023
On the ISS Property of the Gradient Flow for Single Hidden-Layer Neural
  Networks with Linear Activations
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
17
2
0
17 May 2023
Deep networks for system identification: a Survey
Deep networks for system identification: a Survey
G. Pillonetto
Aleksandr Aravkin
Daniel Gedon
L. Ljung
Antônio H. Ribeiro
Thomas B. Schon
OOD
37
35
0
30 Jan 2023
Surprises in adversarially-trained linear regression
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
Unsolved Problems in ML Safety
Dan Hendrycks
Nicholas Carlini
John Schulman
Jacob Steinhardt
186
273
0
28 Sep 2021
1