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2007.04028
Cited By
How benign is benign overfitting?
International Conference on Learning Representations (ICLR), 2020
8 July 2020
Amartya Sanyal
P. Dokania
Varun Kanade
Juil Sock
NoLa
AAML
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Papers citing
"How benign is benign overfitting?"
41 / 41 papers shown
How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime?
Wei Huang
Andi Han
Yujin Song
Yilan Chen
Denny Wu
Difan Zou
Taiji Suzuki
NoLa
MLT
256
3
0
20 Oct 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond
Qiongxiu Li
Xiaoyu Luo
Yiyi Chen
Johannes Bjerva
592
8
0
10 Mar 2025
Scanning Trojaned Models Using Out-of-Distribution Samples
Hossein Mirzaei
Ali Ansari
Bahar Dibaei Nia
Mojtaba Nafez
Moein Madadi
...
Kian Shamsaie
Mahdi Hajialilue
Jafar Habibi
Mohammad Sabokrou
M. Rohban
OODD
401
5
0
28 Jan 2025
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation
Amartya Sanyal
Yaxi Hu
Yaodong Yu
Yian Ma
Yixin Wang
Bernhard Schölkopf
OODD
258
7
0
27 Jun 2024
Potion: Towards Poison Unlearning
Stefan Schoepf
Jack Foster
Alexandra Brintrup
AAML
MU
311
12
0
13 Jun 2024
Corrective Machine Unlearning
Shashwat Goel
Christian Schroeder de Witt
Juil Sock
Ponnurangam Kumaraguru
Amartya Sanyal
OnRL
318
24
0
21 Feb 2024
Memorisation Cartography: Mapping out the Memorisation-Generalisation Continuum in Neural Machine Translation
Verna Dankers
Ivan Titov
Dieuwke Hupkes
291
5
0
09 Nov 2023
Outlier Robust Adversarial Training
Asian Conference on Machine Learning (ACML), 2023
Shu Hu
Zhenhuan Yang
X. Wang
Yiming Ying
Siwei Lyu
AAML
259
10
0
10 Sep 2023
Optimal Rate of Kernel Regression in Large Dimensions
Weihao Lu
Hao Zhang
Yicheng Li
Manyun Xu
Qian Lin
294
6
0
08 Sep 2023
On the ISS Property of the Gradient Flow for Single Hidden-Layer Neural Networks with Linear Activations
A. C. B. D. Oliveira
Milad Siami
Eduardo Sontag
296
2
0
17 May 2023
Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks
Jingfeng Zhang
Bo Song
Bo Han
Lei Liu
Gang Niu
Masashi Sugiyama
AAML
203
2
0
30 Apr 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
409
16
0
17 Mar 2023
Combating Exacerbated Heterogeneity for Robust Models in Federated Learning
International Conference on Learning Representations (ICLR), 2023
Jianing Zhu
Jiangchao Yao
Tongliang Liu
Quanming Yao
Jianliang Xu
Bo Han
FedML
226
8
0
01 Mar 2023
Strong inductive biases provably prevent harmless interpolation
International Conference on Learning Representations (ICLR), 2023
Michael Aerni
Marco Milanta
Konstantin Donhauser
Fanny Yang
301
10
0
18 Jan 2023
Maximum Likelihood Distillation for Robust Modulation Classification
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022
Javier Maroto
Gérôme Bovet
P. Frossard
AAML
130
8
0
01 Nov 2022
Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks
Neural Information Processing Systems (NeurIPS), 2022
Jianan Zhou
Jianing Zhu
Jingfeng Zhang
Tongliang Liu
Gang Niu
Bo Han
Masashi Sugiyama
AAML
203
12
0
01 Nov 2022
The Curious Case of Benign Memorization
International Conference on Learning Representations (ICLR), 2022
Sotiris Anagnostidis
Gregor Bachmann
Lorenzo Noci
Thomas Hofmann
AAML
396
13
0
25 Oct 2022
Learning Sample Reweighting for Accuracy and Adversarial Robustness
Chester Holtz
Tsui-Wei Weng
Zhengchao Wan
OOD
310
6
0
20 Oct 2022
Membership Inference Attacks via Adversarial Examples
Hamid Jalalzai
Elie Kadoche
Rémi Leluc
Vincent Plassier
AAML
FedML
MIACV
251
10
0
27 Jul 2022
One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training
International Conference on Machine Learning (ICML), 2022
Sekitoshi Kanai
Shin'ya Yamaguchi
Masanori Yamada
Hiroshi Takahashi
Kentaro Ohno
Yasutoshi Ida
AAML
339
13
0
21 Jul 2022
A law of adversarial risk, interpolation, and label noise
International Conference on Learning Representations (ICLR), 2022
Daniel Paleka
Amartya Sanyal
NoLa
AAML
389
10
0
08 Jul 2022
Removing Batch Normalization Boosts Adversarial Training
International Conference on Machine Learning (ICML), 2022
Haotao Wang
Aston Zhang
Shuai Zheng
Xingjian Shi
Mu Li
Zinan Lin
288
51
0
04 Jul 2022
Catastrophic overfitting can be induced with discriminative non-robust features
Guillermo Ortiz-Jiménez
Pau de Jorge
Amartya Sanyal
Adel Bibi
P. Dokania
P. Frossard
Grégory Rogez
Juil Sock
AAML
175
3
0
16 Jun 2022
Memorization-Dilation: Modeling Neural Collapse Under Label Noise
Duc Anh Nguyen
Ron Levie
Julian Lienen
Gitta Kutyniok
Eyke Hüllermeier
302
2
0
11 Jun 2022
How unfair is private learning ?
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Amartya Sanyal
Yaxian Hu
Fanny Yang
FaML
FedML
434
27
0
08 Jun 2022
XPASC: Measuring Generalization in Weak Supervision by Explainability and Association
Luisa März
Ehsaneddin Asgari
Fabienne Braune
Franziska Zimmermann
Benjamin Roth
158
0
0
03 Jun 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes
Elvis Dohmatob
A. Bietti
AAML
418
15
0
22 Mar 2022
On the benefits of knowledge distillation for adversarial robustness
Javier Maroto
Guillermo Ortiz-Jiménez
P. Frossard
AAML
FedML
300
28
0
14 Mar 2022
Why adversarial training can hurt robust accuracy
International Conference on Learning Representations (ICLR), 2022
Jacob Clarysse
Julia Hörrmann
Fanny Yang
AAML
290
22
0
03 Mar 2022
Benefit of Interpolation in Nearest Neighbor Algorithms
SIAM Journal on Mathematics of Data Science (SIMODS), 2019
Yue Xing
Qifan Song
Guang Cheng
346
44
0
23 Feb 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition
International Conference on Machine Learning (ICML), 2022
Tianyu Pang
Min Lin
Xiao Yang
Junyi Zhu
Shuicheng Yan
552
163
0
21 Feb 2022
Benign Overfitting in Adversarially Robust Linear Classification
Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Jinghui Chen
Yuan Cao
Quanquan Gu
AAML
SILM
300
12
0
31 Dec 2021
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
Chen Liu
Zhichao Huang
Mathieu Salzmann
Tong Zhang
Sabine Süsstrunk
AAML
395
15
0
14 Dec 2021
Bridged Adversarial Training
Neural Networks (NN), 2021
Hoki Kim
Woojin Lee
Sungyoon Lee
Jaewook Lee
AAML
GAN
178
10
0
25 Aug 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
295
16
0
05 Aug 2021
Towards the Memorization Effect of Neural Networks in Adversarial Training
Han Xu
Xiaorui Liu
Wentao Wang
Wenbiao Ding
Zhongqin Wu
Zitao Liu
Anil K. Jain
Shucheng Zhou
TDI
AAML
261
7
0
09 Jun 2021
Exploring Memorization in Adversarial Training
International Conference on Learning Representations (ICLR), 2021
Yinpeng Dong
Ke Xu
Xiao Yang
Tianyu Pang
Zhijie Deng
Hang Su
Jun Zhu
TDI
172
83
0
03 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels
Jingfeng Zhang
Xilie Xu
Bo Han
Tongliang Liu
Gang Niu
Li-zhen Cui
Masashi Sugiyama
NoLa
AAML
265
9
0
31 May 2021
Multiplicative Reweighting for Robust Neural Network Optimization
SIAM Journal of Imaging Sciences (SIAM J. Imaging Sci.), 2021
Noga Bar
Tomer Koren
Raja Giryes
OOD
NoLa
832
8
0
24 Feb 2021
How Does a Neural Network's Architecture Impact Its Robustness to Noisy Labels?
Neural Information Processing Systems (NeurIPS), 2020
Jingling Li
Mozhi Zhang
Keyulu Xu
John P. Dickerson
Jimmy Ba
OOD
NoLa
340
23
0
23 Dec 2020
What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation
Neural Information Processing Systems (NeurIPS), 2020
Vitaly Feldman
Chiyuan Zhang
TDI
704
597
0
09 Aug 2020
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