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Vulnerability Under Adversarial Machine Learning: Bias or Variance?

Vulnerability Under Adversarial Machine Learning: Bias or Variance?

1 August 2020
Hossein Aboutalebi
M. Shafiee
Michelle Karg
C. Scharfenberger
A. Wong
    AAML
ArXiv (abs)PDFHTML

Papers citing "Vulnerability Under Adversarial Machine Learning: Bias or Variance?"

3 / 3 papers shown
Title
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models
Alireza Aghabagherloo
Aydin Abadi
Sumanta Sarkar
Vishnu Asutosh Dasu
Bart Preneel
AAML
125
1
0
01 Apr 2025
Understanding Generalization in Adversarial Training via the
  Bias-Variance Decomposition
Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition
Yaodong Yu
Zitong Yang
Yan Sun
Jacob Steinhardt
Yi-An Ma
64
17
0
17 Mar 2021
How Much Can We Really Trust You? Towards Simple, Interpretable Trust
  Quantification Metrics for Deep Neural Networks
How Much Can We Really Trust You? Towards Simple, Interpretable Trust Quantification Metrics for Deep Neural Networks
A. Wong
Xiao Yu Wang
Andrew Hryniowski
62
23
0
12 Sep 2020
1