Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2010.11213
Cited By
v1
v2 (latest)
Precise Statistical Analysis of Classification Accuracies for Adversarial Training
21 October 2020
Adel Javanmard
Mahdi Soltanolkotabi
AAML
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Precise Statistical Analysis of Classification Accuracies for Adversarial Training"
40 / 40 papers shown
Kernel Learning with Adversarial Features: Numerical Efficiency and Adaptive Regularization
Antônio H. Ribeiro
David Vävinggren
Dave Zachariah
Thomas B. Schon
Francis Bach
AAML
200
1
0
23 Oct 2025
A Fundamental Accuracy--Robustness Trade-off in Regression and Classification
Sohail Bahmani
286
0
0
01 Jul 2025
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Kasimir Tanner
Matteo Vilucchio
Bruno Loureiro
Florent Krzakala
AAML
483
4
0
31 Dec 2024
Robust Feature Learning for Multi-Index Models in High Dimensions
International Conference on Learning Representations (ICLR), 2024
Alireza Mousavi-Hosseini
Adel Javanmard
Murat A. Erdogdu
OOD
AAML
566
5
0
21 Oct 2024
Efficient Optimization Algorithms for Linear Adversarial Training
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Antônio H. Ribeiro
Thomas B. Schon
Dave Zahariah
Francis Bach
AAML
605
3
0
16 Oct 2024
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
International Conference on Learning Representations (ICLR), 2024
Binghui Li
Yuanzhi Li
OOD
440
11
0
11 Oct 2024
Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need
Neural Information Processing Systems (NeurIPS), 2024
Xianlong Wang
Minghui Li
Wei Liu
Hangtao Zhang
Shengshan Hu
Yechao Zhang
Ziqi Zhou
Hai Jin
3DPC
MU
322
15
0
04 Oct 2024
High-dimensional (Group) Adversarial Training in Linear Regression
Yiling Xie
Xiaoming Huo
304
5
0
22 May 2024
Fermi-Bose Machine achieves both generalization and adversarial robustness
Mingshan Xie
Yuchen Wang
Haiping Huang
AAML
234
1
0
21 Apr 2024
H
H
H
-Consistency Guarantees for Regression
Anqi Mao
M. Mohri
Yutao Zhong
437
16
0
28 Mar 2024
Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance
Chiraag Kaushik
Ran Liu
Chi-Heng Lin
Amrit Khera
Matthew Y Jin
Wenrui Ma
Vidya Muthukumar
Eva L. Dyer
318
4
0
18 Feb 2024
Asymptotic Behavior of Adversarial Training Estimator under
ℓ
∞
\ell_\infty
ℓ
∞
-Perturbation
Yiling Xie
Xiaoming Huo
327
3
0
27 Jan 2024
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Yue Xing
Xiaofeng Lin
Qifan Song
Yi Tian Xu
Belinda Zeng
Guang Cheng
SSL
288
0
0
26 Jan 2024
Corrupting Convolution-based Unlearnable Datasets with Pixel-based Image Transformations
Xianlong Wang
Shengshan Hu
Minghui Li
Zhifei Yu
Ziqi Zhou
Leo Yu Zhang
AAML
312
6
0
30 Nov 2023
Regularized Linear Regression for Binary Classification
International Symposium on Information Theory (ISIT), 2023
D. Akhtiamov
Reza Ghane
Babak Hassibi
NoLa
250
10
0
03 Nov 2023
Regularization properties of adversarially-trained linear regression
Neural Information Processing Systems (NeurIPS), 2023
Antônio H. Ribeiro
Dave Zachariah
Francis Bach
Thomas B. Schön
AAML
313
19
0
16 Oct 2023
Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization
Neural Information Processing Systems (NeurIPS), 2023
Adel Javanmard
Vahab Mirrokni
484
3
0
06 Oct 2023
Universality of max-margin classifiers
Andrea Montanari
Feng Ruan
Basil Saeed
Youngtak Sohn
284
5
0
29 Sep 2023
Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models
Changyu Liu
Yuling Jiao
Junhui Wang
Jian Huang
AAML
236
2
0
02 Sep 2023
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms
Elvis Dohmatob
M. Scetbon
AAML
OOD
233
1
0
01 Aug 2023
CUDA: Convolution-based Unlearnable Datasets
Computer Vision and Pattern Recognition (CVPR), 2023
Vinu Sankar Sadasivan
Mahdi Soltanolkotabi
Soheil Feizi
MU
347
33
0
07 Mar 2023
The Generalization Error of Stochastic Mirror Descent on Over-Parametrized Linear Models
D. Akhtiamov
B. Hassibi
187
0
0
18 Feb 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels
International Conference on Machine Learning (ICML), 2023
Simone Bombari
Shayan Kiyani
Marco Mondelli
AAML
514
13
0
03 Feb 2023
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
M. Scetbon
Elvis Dohmatob
AAML
259
5
0
31 Jan 2023
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria
Journal of machine learning research (JMLR), 2022
Tengyuan Liang
509
3
0
05 Dec 2022
Margin-based sampling in high dimensions: When being active is less efficient than staying passive
International Conference on Machine Learning (ICML), 2022
A. Tifrea
Jacob Clarysse
Fanny Yang
316
5
0
01 Dec 2022
Surprises in adversarially-trained linear regression
Antônio H. Ribeiro
Dave Zachariah
Thomas B. Schon
AAML
495
3
0
25 May 2022
Overparameterized Linear Regression under Adversarial Attacks
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022
Antônio H. Ribeiro
Thomas B. Schon
AAML
231
25
0
13 Apr 2022
A Modern Theory for High-dimensional Cox Regression Models
Xianyang Zhang
Huijuan Zhou
Hanxuan Ye
214
8
0
03 Apr 2022
Unlabeled Data Help: Minimax Analysis and Adversarial Robustness
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Yue Xing
Qifan Song
Guang Cheng
200
4
0
14 Feb 2022
Can Adversarial Training Be Manipulated By Non-Robust Features?
Neural Information Processing Systems (NeurIPS), 2022
Lue Tao
Lei Feng
Jianguo Huang
Jinfeng Yi
Sheng-Jun Huang
Songcan Chen
AAML
768
17
0
31 Jan 2022
Benign Overfitting in Adversarially Robust Linear Classification
Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Jinghui Chen
Yuan Cao
Quanquan Gu
AAML
SILM
303
12
0
31 Dec 2021
Adversarial robustness for latent models: Revisiting the robust-standard accuracies tradeoff
Operational Research (OR), 2021
Adel Javanmard
M. Mehrabi
AAML
307
6
0
22 Oct 2021
Classification and Adversarial examples in an Overparameterized Linear Model: A Signal Processing Perspective
Adhyyan Narang
Vidya Muthukumar
A. Sahai
SILM
AAML
240
1
0
27 Sep 2021
Interpolation can hurt robust generalization even when there is no noise
Neural Information Processing Systems (NeurIPS), 2021
Konstantin Donhauser
Alexandru cTifrea
Michael Aerni
Reinhard Heckel
Fanny Yang
298
16
0
05 Aug 2021
Understanding Generalization in Adversarial Training via the Bias-Variance Decomposition
Yaodong Yu
Zitong Yang
Guang Cheng
Jacob Steinhardt
Yi-An Ma
367
20
0
17 Mar 2021
Bridging the Gap Between Adversarial Robustness and Optimization Bias
Fartash Faghri
Sven Gowal
C. N. Vasconcelos
David J. Fleet
Fabian Pedregosa
Nicolas Le Roux
AAML
448
8
0
17 Feb 2021
Fundamental Tradeoffs in Distributionally Adversarial Training
International Conference on Machine Learning (ICML), 2021
M. Mehrabi
Adel Javanmard
Ryan A. Rossi
Anup B. Rao
Tung Mai
AAML
217
19
0
15 Jan 2021
Robustifying Binary Classification to Adversarial Perturbation
Fariborz Salehi
B. Hassibi
AAML
189
0
0
29 Oct 2020
Asymptotic Behavior of Adversarial Training in Binary Classification
Hossein Taheri
Ramtin Pedarsani
Christos Thrampoulidis
AAML
474
16
0
26 Oct 2020
1
Page 1 of 1
