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Convergence of Adversarial Training in Overparametrized Neural Networks
v1v2 (latest)

Convergence of Adversarial Training in Overparametrized Neural Networks

Neural Information Processing Systems (NeurIPS), 2019
19 June 2019
Ruiqi Gao
Tianle Cai
Haochuan Li
Liwei Wang
Cho-Jui Hsieh
Jason D. Lee
    AAML
ArXiv (abs)PDFHTML

Papers citing "Convergence of Adversarial Training in Overparametrized Neural Networks"

50 / 78 papers shown
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces
Geometry of Neural Reinforcement Learning in Continuous State and Action SpacesInternational Conference on Learning Representations (ICLR), 2025
Saket Tiwari
Omer Gottesman
George Konidaris
226
3
0
28 Jul 2025
Understanding Inverse Reinforcement Learning under Overparameterization: Non-Asymptotic Analysis and Global Optimality
Understanding Inverse Reinforcement Learning under Overparameterization: Non-Asymptotic Analysis and Global OptimalityInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Ruijia Zhang
Siliang Zeng
Chenliang Li
Alfredo García
Mingyi Hong
304
0
0
22 Mar 2025
Attack Anything: Blind DNNs via Universal Background Adversarial Attack
Attack Anything: Blind DNNs via Universal Background Adversarial Attack
Jiawei Lian
Shaohui Mei
X. Wang
Yi Wang
L. Wang
Yingjie Lu
Mingyang Ma
Lap-Pui Chau
AAML
562
3
0
17 Aug 2024
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds
Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds
Hong Ye Tan
Subhadip Mukherjee
Junqi Tang
Carola-Bibiane Schönlieb
309
0
0
13 Aug 2024
Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls
Distributionally and Adversarially Robust Logistic Regression via Intersecting Wasserstein Balls
Aras Selvi
Eleonora Kreacic
Mohsen Ghassemi
Vamsi K. Potluru
T. Balch
Manuela Veloso
521
2
0
18 Jul 2024
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis
Zhang Chen
Christian Scano
Srishti Gupta
Xiaoyi Feng
Zhaoqiang Xia
...
Maura Pintor
Luca Oneto
Ambra Demontis
Battista Biggio
Fabio Roli
AAML
341
2
0
14 Jun 2024
Spectral regularization for adversarially-robust representation learning
Spectral regularization for adversarially-robust representation learning
Sheng Yang
Jacob A. Zavatone-Veth
Cengiz Pehlevan
AAMLOOD
323
3
0
27 May 2024
Nonparametric Teaching of Implicit Neural Representations
Nonparametric Teaching of Implicit Neural RepresentationsInternational Conference on Machine Learning (ICML), 2024
Chen Zhang
Steven Tin Sui Luo
Jason Chun Lok Li
Yik-Chung Wu
Ngai Wong
280
10
0
17 May 2024
Robust NAS under adversarial training: benchmark, theory, and beyond
Robust NAS under adversarial training: benchmark, theory, and beyond
Yongtao Wu
Fanghui Liu
Carl-Johann Simon-Gabriel
Grigorios G. Chrysos
Volkan Cevher
AAMLOOD
277
9
0
19 Mar 2024
The Surprising Harmfulness of Benign Overfitting for Adversarial
  Robustness
The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness
Yifan Hao
Tong Zhang
AAML
508
6
0
19 Jan 2024
Defenses in Adversarial Machine Learning: A Survey
Defenses in Adversarial Machine Learning: A Survey
Baoyuan Wu
Shaokui Wei
Mingli Zhu
Meixi Zheng
Zihao Zhu
Ruotong Wang
Hongrui Chen
Danni Yuan
Li Liu
Qingshan Liu
AAML
306
22
0
13 Dec 2023
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK
  Approach
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK ApproachIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2023
Shaopeng Fu
Haiyan Zhao
AAML
382
3
0
09 Oct 2023
Generating Less Certain Adversarial Examples Improves Robust Generalization
Generating Less Certain Adversarial Examples Improves Robust Generalization
Minxing Zhang
Michael Backes
Xiao Zhang
AAML
553
1
0
06 Oct 2023
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for
  General Norms
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms
Elvis Dohmatob
M. Scetbon
AAMLOOD
199
1
0
01 Aug 2023
Understanding Noise-Augmented Training for Randomized Smoothing
Understanding Noise-Augmented Training for Randomized Smoothing
Ambar Pal
Jeremias Sulam
AAML
361
7
0
08 May 2023
Understanding Overfitting in Adversarial Training via Kernel Regression
Understanding Overfitting in Adversarial Training via Kernel Regression
Teng Zhang
Kang Li
180
2
0
13 Apr 2023
TRAK: Attributing Model Behavior at Scale
TRAK: Attributing Model Behavior at ScaleInternational Conference on Machine Learning (ICML), 2023
Sung Min Park
Kristian Georgiev
Andrew Ilyas
Guillaume Leclerc
Aleksander Madry
TDI
400
230
0
24 Mar 2023
NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial
  Attacks
NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial AttacksIEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2023
Wen-Xi Tan
Justus Renkhoff
Alvaro Velasquez
Ziyu Wang
Lu Li
Jian Wang
Shuteng Niu
Fan Yang
Yongxin Liu
Haoze Song
AAML
185
8
0
09 Mar 2023
Exploring Adversarial Attacks on Neural Networks: An Explainable
  Approach
Exploring Adversarial Attacks on Neural Networks: An Explainable ApproachIEEE International Performance, Computing, and Communications Conference (IPCCC), 2022
Justus Renkhoff
Wenkai Tan
Alvaro Velasquez
William Yichen Wang
Yongxin Liu
Jian Wang
Shuteng Niu
Lejla Begic Fazlic
Guido Dartmann
Haoze Song
AAML
181
7
0
08 Mar 2023
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function
  Approximation
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function ApproximationInternational Conference on Learning Representations (ICLR), 2023
Thanh Nguyen-Tang
R. Arora
OffRL
239
6
0
24 Feb 2023
Adaptive Smoothness-weighted Adversarial Training for Multiple
  Perturbations with Its Stability Analysis
Adaptive Smoothness-weighted Adversarial Training for Multiple Perturbations with Its Stability Analysis
Jiancong Xiao
Zeyu Qin
Yanbo Fan
Baoyuan Wu
Jue Wang
Zhimin Luo
AAML
257
8
0
02 Oct 2022
Characterizing Internal Evasion Attacks in Federated Learning
Characterizing Internal Evasion Attacks in Federated LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Taejin Kim
Shubhranshu Singh
Nikhil Madaan
Carlee Joe-Wong
FedML
240
16
0
17 Sep 2022
Robustness in deep learning: The good (width), the bad (depth), and the
  ugly (initialization)
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization)Neural Information Processing Systems (NeurIPS), 2022
Zhenyu Zhu
Fanghui Liu
Grigorios G. Chrysos
Volkan Cevher
352
23
0
15 Sep 2022
Federated Adversarial Learning: A Framework with Convergence Analysis
Federated Adversarial Learning: A Framework with Convergence AnalysisInternational Conference on Machine Learning (ICML), 2022
Xiaoxiao Li
Zhao Song
Jiaming Yang
FedML
304
33
0
07 Aug 2022
BiFeat: Supercharge GNN Training via Graph Feature Quantization
BiFeat: Supercharge GNN Training via Graph Feature Quantization
Yuxin Ma
Ping Gong
Jun Yi
Z. Yao
Cheng-rong Li
Yuxiong He
Feng Yan
GNN
134
7
0
29 Jul 2022
Understanding Robust Learning through the Lens of Representation
  Similarities
Understanding Robust Learning through the Lens of Representation SimilaritiesNeural Information Processing Systems (NeurIPS), 2022
Christian Cianfarani
A. Bhagoji
Vikash Sehwag
Ben Y. Zhao
Prateek Mittal
Haitao Zheng
OOD
324
18
0
20 Jun 2022
Adversarial Robustness is at Odds with Lazy Training
Adversarial Robustness is at Odds with Lazy TrainingNeural Information Processing Systems (NeurIPS), 2022
Yunjuan Wang
Enayat Ullah
Poorya Mianjy
R. Arora
SILMAAML
297
12
0
18 Jun 2022
Provably Efficient Offline Reinforcement Learning with Trajectory-Wise
  Reward
Provably Efficient Offline Reinforcement Learning with Trajectory-Wise RewardIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Tengyu Xu
Yue Wang
Shaofeng Zou
Yingbin Liang
OffRL
240
15
0
13 Jun 2022
Distributed Adversarial Training to Robustify Deep Neural Networks at
  Scale
Distributed Adversarial Training to Robustify Deep Neural Networks at ScaleConference on Uncertainty in Artificial Intelligence (UAI), 2022
Gaoyuan Zhang
Songtao Lu
Yihua Zhang
Xiangyi Chen
Pin-Yu Chen
Quanfu Fan
Lee Martie
L. Horesh
Min-Fong Hong
Sijia Liu
OOD
273
14
0
13 Jun 2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of
  Expressive Power
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive PowerNeural Information Processing Systems (NeurIPS), 2022
Binghui Li
Jikai Jin
Han Zhong
John E. Hopcroft
Liwei Wang
OOD
298
33
0
27 May 2022
Randomly Initialized One-Layer Neural Networks Make Data Linearly
  Separable
Randomly Initialized One-Layer Neural Networks Make Data Linearly Separable
Promit Ghosal
Srinath Mahankali
Yihang Sun
MLT
177
5
0
24 May 2022
Robust Sensible Adversarial Learning of Deep Neural Networks for Image
  Classification
Robust Sensible Adversarial Learning of Deep Neural Networks for Image ClassificationAnnals of Applied Statistics (AOAS), 2022
Jungeum Kim
Tianlin Li
OODAAML
119
3
0
20 May 2022
Origins of Low-dimensional Adversarial Perturbations
Origins of Low-dimensional Adversarial PerturbationsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Elvis Dohmatob
Chuan Guo
Morgane Goibert
AAML
200
4
0
25 Mar 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different
  Learning Regimes
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes
Elvis Dohmatob
A. Bietti
AAML
367
15
0
22 Mar 2022
On the Convergence of Certified Robust Training with Interval Bound
  Propagation
On the Convergence of Certified Robust Training with Interval Bound PropagationInternational Conference on Learning Representations (ICLR), 2022
Yihan Wang
Zhouxing Shi
Quanquan Gu
Cho-Jui Hsieh
160
10
0
16 Mar 2022
A Law of Robustness beyond Isoperimetry
A Law of Robustness beyond IsoperimetryInternational Conference on Machine Learning (ICML), 2022
Yihan Wu
Heng Huang
Hongyang R. Zhang
OOD
183
7
0
23 Feb 2022
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial
  Robustness
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial RobustnessInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Beomsu Kim
Junghoon Seo
AAML
200
0
0
21 Feb 2022
Finding Dynamics Preserving Adversarial Winning Tickets
Finding Dynamics Preserving Adversarial Winning TicketsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Xupeng Shi
Pengfei Zheng
Adam Ding
Yuan Gao
Weizhong Zhang
AAML
258
1
0
14 Feb 2022
Towards Adversarially Robust Deep Image Denoising
Towards Adversarially Robust Deep Image DenoisingInternational Joint Conference on Artificial Intelligence (IJCAI), 2022
Hanshu Yan
Jingfeng Zhang
Jiashi Feng
Masashi Sugiyama
Vincent Y. F. Tan
DiffM
192
19
0
12 Jan 2022
Benign Overfitting in Adversarially Robust Linear Classification
Benign Overfitting in Adversarially Robust Linear ClassificationConference on Uncertainty in Artificial Intelligence (UAI), 2021
Jinghui Chen
Yuan Cao
Quanquan Gu
AAMLSILM
215
11
0
31 Dec 2021
A Review of Adversarial Attack and Defense for Classification Methods
A Review of Adversarial Attack and Defense for Classification Methods
Yao Li
Minhao Cheng
Cho-Jui Hsieh
T. C. Lee
AAML
199
89
0
18 Nov 2021
On Reward-Free RL with Kernel and Neural Function Approximations:
  Single-Agent MDP and Markov Game
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Delin Qu
Jieping Ye
Zhaoran Wang
Zhuoran Yang
OffRL
237
25
0
19 Oct 2021
Provable Regret Bounds for Deep Online Learning and Control
Provable Regret Bounds for Deep Online Learning and Control
Xinyi Chen
Edgar Minasyan
Jason D. Lee
Elad Hazan
361
6
0
15 Oct 2021
Robust Generalization of Quadratic Neural Networks via Function
  Identification
Robust Generalization of Quadratic Neural Networks via Function Identification
Kan Xu
Hamsa Bastani
Osbert Bastani
OOD
238
9
0
22 Sep 2021
Improving the Robustness of Adversarial Attacks Using an
  Affine-Invariant Gradient Estimator
Improving the Robustness of Adversarial Attacks Using an Affine-Invariant Gradient Estimator
Wenzhao Xiang
Hang Su
Chang-rui Liu
Yandong Guo
Shibao Zheng
AAML
148
12
0
13 Sep 2021
Advances in adversarial attacks and defenses in computer vision: A
  survey
Advances in adversarial attacks and defenses in computer vision: A survey
Naveed Akhtar
Lin Wang
Navid Kardan
M. Shah
AAML
480
299
0
01 Aug 2021
Taxonomy of Machine Learning Safety: A Survey and Primer
Taxonomy of Machine Learning Safety: A Survey and PrimerACM Computing Surveys (CSUR), 2021
Sina Mohseni
Haotao Wang
Zhiding Yu
Chaowei Xiao
Zinan Lin
J. Yadawa
314
47
0
09 Jun 2021
Exploring Memorization in Adversarial Training
Exploring Memorization in Adversarial TrainingInternational Conference on Learning Representations (ICLR), 2021
Yinpeng Dong
Ke Xu
Xiao Yang
Tianyu Pang
Zhijie Deng
Hang Su
Jun Zhu
TDI
138
83
0
03 Jun 2021
A Universal Law of Robustness via Isoperimetry
A Universal Law of Robustness via IsoperimetryNeural Information Processing Systems (NeurIPS), 2021
Sébastien Bubeck
Mark Sellke
347
230
0
26 May 2021
Adversarial Training for Gradient Descent: Analysis Through its
  Continuous-time Approximation
Adversarial Training for Gradient Descent: Analysis Through its Continuous-time Approximation
Haotian Gu
Xin Guo
Xinyu Li
200
2
0
17 May 2021
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