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On the Hardness of Robustness Transfer: A Perspective from Rademacher
  Complexity over Symmetric Difference Hypothesis Space

On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space

23 February 2023
Yuyang Deng
Nidham Gazagnadou
Junyuan Hong
M. Mahdavi
Lingjuan Lyu
    AAML
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Papers citing "On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space"

12 / 12 papers shown
Title
When Does Contrastive Learning Preserve Adversarial Robustness from
  Pretraining to Finetuning?
When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
Lijie Fan
Sijia Liu
Pin-Yu Chen
Gaoyuan Zhang
Chuang Gan
AAML
VLM
59
123
0
01 Nov 2021
Adversarial Training Helps Transfer Learning via Better Representations
Adversarial Training Helps Transfer Learning via Better Representations
Zhun Deng
Linjun Zhang
Kailas Vodrahalli
Kenji Kawaguchi
James Zou
GAN
79
54
0
18 Jun 2021
On Localized Discrepancy for Domain Adaptation
On Localized Discrepancy for Domain Adaptation
Yuchen Zhang
Mingsheng Long
Jianmin Wang
Michael I. Jordan
54
18
0
14 Aug 2020
Do Adversarially Robust ImageNet Models Transfer Better?
Do Adversarially Robust ImageNet Models Transfer Better?
Hadi Salman
Andrew Ilyas
Logan Engstrom
Ashish Kapoor
Aleksander Madry
65
424
0
16 Jul 2020
Lower Bounds for Adversarially Robust PAC Learning
Lower Bounds for Adversarially Robust PAC Learning
Dimitrios I. Diochnos
Saeed Mahloujifar
Mohammad Mahmoody
AAML
50
26
0
13 Jun 2019
VC Classes are Adversarially Robustly Learnable, but Only Improperly
VC Classes are Adversarially Robustly Learnable, but Only Improperly
Omar Montasser
Steve Hanneke
Nathan Srebro
29
139
0
12 Feb 2019
Adversarial Risk and Robustness: General Definitions and Implications
  for the Uniform Distribution
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution
Dimitrios I. Diochnos
Saeed Mahloujifar
Mohammad Mahmoody
AAML
41
72
0
29 Oct 2018
Unsupervised Domain Adaptation Based on Source-guided Discrepancy
Unsupervised Domain Adaptation Based on Source-guided Discrepancy
Seiichi Kuroki
Nontawat Charoenphakdee
Han Bao
Junya Honda
Issei Sato
Masashi Sugiyama
60
58
0
11 Sep 2018
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
301
12,063
0
19 Jun 2017
Learning Transferable Features with Deep Adaptation Networks
Learning Transferable Features with Deep Adaptation Networks
Mingsheng Long
Yue Cao
Jianmin Wang
Michael I. Jordan
OOD
217
5,196
0
10 Feb 2015
Unsupervised Domain Adaptation by Backpropagation
Unsupervised Domain Adaptation by Backpropagation
Yaroslav Ganin
Victor Lempitsky
OOD
233
6,022
0
26 Sep 2014
Adaptation Algorithm and Theory Based on Generalized Discrepancy
Adaptation Algorithm and Theory Based on Generalized Discrepancy
Corinna Cortes
M. Mohri
Andrés Munoz Medina
74
66
0
07 May 2014
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