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TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical Justification

TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical Justification

10 May 2025
Dongyoon Yang
Jihu Lee
Yongdai Kim
ArXivPDFHTML

Papers citing "TAROT: Towards Essentially Domain-Invariant Robustness with Theoretical Justification"

32 / 32 papers shown
Title
Reliable and Efficient Concept Erasure of Text-to-Image Diffusion Models
Reliable and Efficient Concept Erasure of Text-to-Image Diffusion Models
Chao Gong
Kai-xiang Chen
Zhipeng Wei
Jingjing Chen
Yulong Jiang
DiffM
97
35
0
17 Jul 2024
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings
  for Robust Large Vision-Language Models
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
Christian Schlarmann
Naman D. Singh
Francesco Croce
Matthias Hein
VLM
AAML
76
46
0
19 Feb 2024
Enhancing Adversarial Robustness in Low-Label Regime via Adaptively
  Weighted Regularization and Knowledge Distillation
Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation
Dongyoon Yang
Insung Kong
Yongdai Kim
54
4
0
08 Aug 2023
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models
Chengzhi Mao
Scott Geng
Junfeng Yang
Xin Eric Wang
Carl Vondrick
VLM
82
68
0
14 Dec 2022
SRoUDA: Meta Self-training for Robust Unsupervised Domain Adaptation
SRoUDA: Meta Self-training for Robust Unsupervised Domain Adaptation
Wan-Xuan Zhu
Jia-Li Yin
Bo-Hao Chen
Ximeng Liu
66
6
0
12 Dec 2022
Efficiently Computing Local Lipschitz Constants of Neural Networks via
  Bound Propagation
Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation
Zhouxing Shi
Yihan Wang
Huan Zhang
Zico Kolter
Cho-Jui Hsieh
140
42
0
13 Oct 2022
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean
  Function Perspective
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective
Bohang Zhang
Du Jiang
Di He
Liwei Wang
OOD
66
50
0
04 Oct 2022
Improving Adversarial Robustness by Putting More Regularizations on Less
  Robust Samples
Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples
Dongyoon Yang
Insung Kong
Yongdai Kim
OOD
AAML
38
10
0
07 Jun 2022
The robust way to stack and bag: the local Lipschitz way
The robust way to stack and bag: the local Lipschitz way
Thulasi Tholeti
Sheetal Kalyani
AAML
30
5
0
01 Jun 2022
Exploring Adversarially Robust Training for Unsupervised Domain
  Adaptation
Exploring Adversarially Robust Training for Unsupervised Domain Adaptation
Shao-Yuan Lo
Vishal M. Patel
AAML
63
8
0
18 Feb 2022
Two Wrongs Don't Make a Right: Combating Confirmation Bias in Learning
  with Label Noise
Two Wrongs Don't Make a Right: Combating Confirmation Bias in Learning with Label Noise
Mingcai Chen
Hao Cheng
Yuntao Du
Ming Xu
Wenyu Jiang
Chongjun Wang
NoLa
48
26
0
06 Dec 2021
Adversarial Robustness for Unsupervised Domain Adaptation
Adversarial Robustness for Unsupervised Domain Adaptation
Muhammad Awais
Fengwei Zhou
Hang Xu
Lanqing Hong
Ping Luo
Sung-Ho Bae
Zhenguo Li
63
39
0
02 Sep 2021
Latent Space Regularization for Unsupervised Domain Adaptation in
  Semantic Segmentation
Latent Space Regularization for Unsupervised Domain Adaptation in Semantic Segmentation
F. Barbato
Marco Toldo
Umberto Michieli
Pietro Zanuttigh
59
20
0
06 Apr 2021
Do Wider Neural Networks Really Help Adversarial Robustness?
Do Wider Neural Networks Really Help Adversarial Robustness?
Boxi Wu
Jinghui Chen
Deng Cai
Xiaofei He
Quanquan Gu
AAML
53
95
0
03 Oct 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
Reliable evaluation of adversarial robustness with an ensemble of
  diverse parameter-free attacks
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce
Matthias Hein
AAML
216
1,842
0
03 Mar 2020
Exactly Computing the Local Lipschitz Constant of ReLU Networks
Exactly Computing the Local Lipschitz Constant of ReLU Networks
Matt Jordan
A. Dimakis
50
112
0
02 Mar 2020
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning
Eric Arazo
Diego Ortego
Paul Albert
Noel E. O'Connor
Kevin McGuinness
119
841
0
08 Aug 2019
Are Labels Required for Improving Adversarial Robustness?
Are Labels Required for Improving Adversarial Robustness?
J. Uesato
Jean-Baptiste Alayrac
Po-Sen Huang
Robert Stanforth
Alhussein Fawzi
Pushmeet Kohli
AAML
74
333
0
31 May 2019
Bridging Theory and Algorithm for Domain Adaptation
Bridging Theory and Algorithm for Domain Adaptation
Yuchen Zhang
Tianle Liu
Mingsheng Long
Michael I. Jordan
80
710
0
11 Apr 2019
Support and Invertibility in Domain-Invariant Representations
Support and Invertibility in Domain-Invariant Representations
Fredrik D. Johansson
David Sontag
Rajesh Ranganath
63
162
0
08 Mar 2019
Theoretically Principled Trade-off between Robustness and Accuracy
Theoretically Principled Trade-off between Robustness and Accuracy
Hongyang R. Zhang
Yaodong Yu
Jiantao Jiao
Eric Xing
L. Ghaoui
Michael I. Jordan
132
2,549
0
24 Jan 2019
Moment Matching for Multi-Source Domain Adaptation
Moment Matching for Multi-Source Domain Adaptation
Xingchao Peng
Qinxun Bai
Xide Xia
Zijun Huang
Kate Saenko
Bo Wang
OOD
130
1,791
0
04 Dec 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
219
3,185
0
01 Feb 2018
Spectrally-normalized margin bounds for neural networks
Spectrally-normalized margin bounds for neural networks
Peter L. Bartlett
Dylan J. Foster
Matus Telgarsky
ODL
202
1,217
0
26 Jun 2017
Deep Hashing Network for Unsupervised Domain Adaptation
Deep Hashing Network for Unsupervised Domain Adaptation
Hemanth Venkateswara
José Eusébio
Shayok Chakraborty
S. Panchanathan
OOD
141
2,041
0
22 Jun 2017
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
304
12,063
0
19 Jun 2017
Parseval Networks: Improving Robustness to Adversarial Examples
Parseval Networks: Improving Robustness to Adversarial Examples
Moustapha Cissé
Piotr Bojanowski
Edouard Grave
Yann N. Dauphin
Nicolas Usunier
AAML
136
807
0
28 Apr 2017
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving
Marvin Teichmann
Michael Weber
Johann Marius Zöllner
R. Cipolla
R. Urtasun
SSeg
71
698
0
22 Dec 2016
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
372
9,486
0
28 May 2015
Unsupervised Domain Adaptation by Backpropagation
Unsupervised Domain Adaptation by Backpropagation
Yaroslav Ganin
Victor Lempitsky
OOD
233
6,022
0
26 Sep 2014
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
270
14,918
1
21 Dec 2013
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