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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

14 June 2024
Zhang Chen
Luca Demetrio
Srishti Gupta
Xiaoyi Feng
Zhaoqiang Xia
Antonio Emanuele Cinà
Maura Pintor
Luca Oneto
Ambra Demontis
Battista Biggio
Fabio Roli
    AAML
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Papers citing "Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis"

4 / 4 papers shown
Title
Data Poisoning in Deep Learning: A Survey
Data Poisoning in Deep Learning: A Survey
Pinlong Zhao
Weiyao Zhu
Pengfei Jiao
Di Gao
Ou Wu
AAML
36
0
0
27 Mar 2025
Robustness in deep learning: The good (width), the bad (depth), and the
  ugly (initialization)
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization)
Zhenyu Zhu
Fanghui Liu
Grigorios G. Chrysos
V. Cevher
27
19
0
15 Sep 2022
Exploring Architectural Ingredients of Adversarially Robust Deep Neural
  Networks
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Hanxun Huang
Yisen Wang
S. Erfani
Quanquan Gu
James Bailey
Xingjun Ma
AAML
TPM
44
100
0
07 Oct 2021
An Investigation of Why Overparameterization Exacerbates Spurious
  Correlations
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Percy Liang
144
368
0
09 May 2020
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