Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1810.12272
Cited By
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution
29 October 2018
Dimitrios I. Diochnos
Saeed Mahloujifar
Mohammad Mahmoody
AAML
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution"
50 / 50 papers shown
BERTector: An Intrusion Detection Framework Constructed via Joint-dataset Learning Based on Language Model
Haoyang Hu
Xun Huang
Chenyu Wu
Shiwen Liu
Z. Lian
Shuangquan Zhang
184
0
0
14 Aug 2025
On the Computability of Robust PAC Learning
Annual Conference Computational Learning Theory (COLT), 2024
Pascale Gourdeau
Tosca Lechner
Ruth Urner
370
6
0
14 Jun 2024
Certifying Global Robustness for Deep Neural Networks
You Li
Guannan Zhao
Shuyu Kong
Yunqi He
Hai Zhou
AAML
153
1
0
31 May 2024
Trustworthy Actionable Perturbations
International Conference on Machine Learning (ICML), 2024
Jesse Friedbaum
Sudarshan Adiga
Ravi Tandon
AAML
276
2
0
18 May 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
Yunzhen Feng
Tim G. J. Rudner
Nikolaos Tsilivis
Julia Kempe
AAML
BDL
336
3
0
27 Apr 2024
Faster Repeated Evasion Attacks in Tree Ensembles
Lorenzo Cascioli
Laurens Devos
Ondvrej Kuvzelka
Jesse Davis
AAML
225
1
0
13 Feb 2024
SoK: Pitfalls in Evaluating Black-Box Attacks
Fnu Suya
Anshuman Suri
Tingwei Zhang
Jingtao Hong
Yuan Tian
David Evans
AAML
383
8
0
26 Oct 2023
It Is All About Data: A Survey on the Effects of Data on Adversarial Robustness
ACM Computing Surveys (ACM Comput. Surv.), 2023
Peiyu Xiong
Michael W. Tegegn
Jaskeerat Singh Sarin
Shubhraneel Pal
Julia Rubin
SILM
AAML
375
16
0
17 Mar 2023
On the Hardness of Robustness Transfer: A Perspective from Rademacher Complexity over Symmetric Difference Hypothesis Space
Yuyang Deng
Nidham Gazagnadou
Junyuan Hong
M. Mahdavi
Lingjuan Lyu
AAML
187
5
0
23 Feb 2023
On the Role of Randomization in Adversarially Robust Classification
Neural Information Processing Systems (NeurIPS), 2023
Lucas Gnecco-Heredia
Y. Chevaleyre
Benjamin Négrevergne
Laurent Meunier
Muni Sreenivas Pydi
AAML
283
6
0
14 Feb 2023
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks
Jona Klemenc
Holger Trittenbach
AAML
145
1
0
28 Jan 2023
When are Local Queries Useful for Robust Learning?
Neural Information Processing Systems (NeurIPS), 2022
Pascale Gourdeau
Varun Kanade
Marta Z. Kwiatkowska
J. Worrell
OOD
372
1
0
12 Oct 2022
Adversarial Example Detection in Deployed Tree Ensembles
Laurens Devos
Wannes Meert
Jesse Davis
AAML
144
2
0
27 Jun 2022
Adversarially Robust PAC Learnability of Real-Valued Functions
International Conference on Machine Learning (ICML), 2022
Idan Attias
Steve Hanneke
270
7
0
26 Jun 2022
Virtual Homogeneity Learning: Defending against Data Heterogeneity in Federated Learning
International Conference on Machine Learning (ICML), 2022
Zhenheng Tang
Yonggang Zhang
Shaoshuai Shi
Xinfu He
Bo Han
Xiaowen Chu
FedML
293
98
0
06 Jun 2022
Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks
International Joint Conference on Artificial Intelligence (IJCAI), 2022
Pascale Gourdeau
Varun Kanade
Marta Z. Kwiatkowska
J. Worrell
AAML
199
5
0
12 May 2022
Planting Undetectable Backdoors in Machine Learning Models
IEEE Annual Symposium on Foundations of Computer Science (FOCS), 2022
S. Goldwasser
Michael P. Kim
Vinod Vaikuntanathan
Or Zamir
AAML
190
84
0
14 Apr 2022
Overparameterized Linear Regression under Adversarial Attacks
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022
Antônio H. Ribeiro
Thomas B. Schon
AAML
197
25
0
13 Apr 2022
Deadwooding: Robust Global Pruning for Deep Neural Networks
Sawinder Kaur
Ferdinando Fioretto
Asif Salekin
325
4
0
10 Feb 2022
The Many Faces of Adversarial Risk
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Muni Sreenivas Pydi
Varun Jog
AAML
180
32
0
22 Jan 2022
The Need for Ethical, Responsible, and Trustworthy Artificial Intelligence for Environmental Sciences
A. McGovern
I. Ebert‐Uphoff
D. Gagne
A. Bostrom
279
78
0
15 Dec 2021
Image classifiers can not be made robust to small perturbations
Zheng Dai
David K Gifford
VLM
AAML
194
1
0
07 Dec 2021
On the Existence of the Adversarial Bayes Classifier (Extended Version)
Pranjal Awasthi
Natalie Frank
M. Mohri
421
28
0
03 Dec 2021
Robust Optimal Classification Trees Against Adversarial Examples
AAAI Conference on Artificial Intelligence (AAAI), 2021
D. Vos
S. Verwer
AAML
118
25
0
08 Sep 2021
On the (Un-)Avoidability of Adversarial Examples
Sadia Chowdhury
Ruth Urner
AAML
170
1
0
24 Jun 2021
Enhancing Robustness of Neural Networks through Fourier Stabilization
International Conference on Machine Learning (ICML), 2021
Netanel Raviv
Aidan Kelley
Michael M. Guo
Yevgeny Vorobeychik
AAML
75
13
0
08 Jun 2021
Learning and Certification under Instance-targeted Poisoning
Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Ji Gao
Amin Karbasi
Mohammad Mahmoody
AAML
240
16
0
18 May 2021
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?
International Conference on Learning Representations (ICLR), 2021
Vikash Sehwag
Saeed Mahloujifar
Tinashe Handina
Sihui Dai
Chong Xiang
M. Chiang
Prateek Mittal
OOD
276
146
0
19 Apr 2021
Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
International Conference on Machine Learning (ICML), 2021
A. Bhagoji
Daniel Cullina
Vikash Sehwag
Prateek Mittal
AAML
OOD
211
3
0
16 Apr 2021
Domain Invariant Adversarial Learning
Matan Levi
Idan Attias
A. Kontorovich
AAML
OOD
517
12
0
01 Apr 2021
Improved Estimation of Concentration Under
ℓ
p
\ell_p
ℓ
p
-Norm Distance Metrics Using Half Spaces
International Conference on Learning Representations (ICLR), 2021
Jack Prescott
Xiao Zhang
David Evans
154
5
0
24 Mar 2021
Query complexity of adversarial attacks
International Conference on Machine Learning (ICML), 2020
Grzegorz Gluch
R. Urbanke
AAML
210
8
0
02 Oct 2020
On Data Augmentation and Adversarial Risk: An Empirical Analysis
Hamid Eghbalzadeh
Khaled Koutini
Paul Primus
Verena Haunschmid
Michal Lewandowski
Werner Zellinger
Bernhard A. Moser
Gerhard Widmer
AAML
137
9
0
06 Jul 2020
Black-box Certification and Learning under Adversarial Perturbations
H. Ashtiani
Vinayak Pathak
Ruth Urner
AAML
196
20
0
30 Jun 2020
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Xiao Zhang
Jinghui Chen
Quanquan Gu
David Evans
164
17
0
01 Mar 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models
International Conference on Machine Learning (ICML), 2020
Lin Chen
Yifei Min
Mingrui Zhang
Amin Karbasi
OOD
301
66
0
11 Feb 2020
Statistically Robust Neural Network Classification
Conference on Uncertainty in Artificial Intelligence (UAI), 2019
Benjie Wang
Stefan Webb
Tom Rainforth
OOD
AAML
247
22
0
10 Dec 2019
Adversarial Risk via Optimal Transport and Optimal Couplings
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2019
Muni Sreenivas Pydi
Varun Jog
281
60
0
05 Dec 2019
On Robustness to Adversarial Examples and Polynomial Optimization
Neural Information Processing Systems (NeurIPS), 2019
Pranjal Awasthi
Abhratanu Dutta
Aravindan Vijayaraghavan
OOD
AAML
191
34
0
12 Nov 2019
Lower Bounds on Adversarial Robustness from Optimal Transport
Neural Information Processing Systems (NeurIPS), 2019
A. Bhagoji
Daniel Cullina
Prateek Mittal
OOD
OT
AAML
219
97
0
26 Sep 2019
On the Hardness of Robust Classification
Pascale Gourdeau
Varun Kanade
Marta Z. Kwiatkowska
J. Worrell
151
44
0
12 Sep 2019
A unified view on differential privacy and robustness to adversarial examples
Rafael Pinot
Florian Yger
Cédric Gouy-Pailler
Jamal Atif
AAML
154
19
0
19 Jun 2019
Lower Bounds for Adversarially Robust PAC Learning
International Conference on Machine Learning and Applications (ICMLA), 2019
Dimitrios I. Diochnos
Saeed Mahloujifar
Mohammad Mahmoody
AAML
239
27
0
13 Jun 2019
Adversarial Risk Bounds for Neural Networks through Sparsity based Compression
E. Balda
Arash Behboodi
Niklas Koep
R. Mathar
AAML
178
9
0
03 Jun 2019
Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness
Neural Information Processing Systems (NeurIPS), 2019
Saeed Mahloujifar
Xiao Zhang
Mohammad Mahmoody
David Evans
231
23
0
29 May 2019
Adversarially Robust Learning Could Leverage Computational Hardness
International Conference on Algorithmic Learning Theory (ALT), 2019
Sanjam Garg
S. Jha
Saeed Mahloujifar
Mohammad Mahmoody
AAML
350
24
0
28 May 2019
Theoretical evidence for adversarial robustness through randomization
Rafael Pinot
Laurent Meunier
Alexandre Araujo
H. Kashima
Florian Yger
Cédric Gouy-Pailler
Jamal Atif
AAML
276
88
0
04 Feb 2019
Improved Generalization Bounds for Adversarially Robust Learning
Idan Attias
A. Kontorovich
Yishay Mansour
332
22
0
04 Oct 2018
Can Adversarially Robust Learning Leverage Computational Hardness?
Saeed Mahloujifar
Mohammad Mahmoody
AAML
OOD
136
49
0
02 Oct 2018
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure
Saeed Mahloujifar
Dimitrios I. Diochnos
Mohammad Mahmoody
228
157
0
09 Sep 2018
1
Page 1 of 1
