A Universal Law of Robustness via Isoperimetry

26 May 2021

Papers citing "A Universal Law of Robustness via Isoperimetry"

27 / 27 papers shown

Title
Do Large Language Models (Really) Need Statistical Foundations? Weijie Su 259 0 0 25 May 2025
Spurious Correlations in High Dimensional Regression: The Roles of Regularization, Simplicity Bias and Over-Parameterization Simone Bombari Marco Mondelli 198 0 0 03 Feb 2025
On the uncertainty principle of neural networks Jun-Jie Zhang Dong-xiao Zhang Jian-Nan Chen L. Pang Deyu Meng 103 2 0 17 Jan 2025
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data Binghui Li Yuanzhi Li OOD 64 3 0 11 Oct 2024
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 231 271 0 18 Apr 2021
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 52 331 0 07 Oct 2020
A law of robustness for two-layers neural networks Sébastien Bubeck Yuanzhi Li Dheeraj M. Nagaraj 71 57 0 30 Sep 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 99 801 0 26 Feb 2020
Deep Double Descent: Where Bigger Models and More Data Hurt Preetum Nakkiran Gal Kaplun Yamini Bansal Tristan Yang Boaz Barak Ilya Sutskever 121 942 0 04 Dec 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 83 635 0 14 Aug 2019
Benign Overfitting in Linear Regression Peter L. Bartlett Philip M. Long Gábor Lugosi Alexander Tsigler MLT 80 776 0 26 Jun 2019
Convergence of Adversarial Training in Overparametrized Neural Networks Ruiqi Gao Tianle Cai Haochuan Li Liwei Wang Cho-Jui Hsieh Jason D. Lee AAML 96 109 0 19 Jun 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 232 1,650 0 28 Dec 2018
On Computation and Generalization of GANs with Spectrum Control Haoming Jiang Zhehui Chen Minshuo Chen Feng Liu Dingding Wang T. Zhao 36 6 0 28 Dec 2018
Rademacher Complexity for Adversarially Robust Generalization Dong Yin Kannan Ramchandran Peter L. Bartlett AAML 89 260 0 29 Oct 2018
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 113 118 0 17 Oct 2018
Estimating the intrinsic dimension of datasets by a minimal neighborhood information Elena Facco M. d’Errico Alex Rodriguez Alessandro Laio 46 327 0 19 Mar 2018
Sensitivity and Generalization in Neural Networks: an Empirical Study Roman Novak Yasaman Bahri Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein AAML 93 440 0 23 Feb 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 155 4,440 0 16 Feb 2018
Spectrally-normalized margin bounds for neural networks Peter L. Bartlett Dylan J. Foster Matus Telgarsky ODL 202 1,220 0 26 Jun 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 307 12,069 0 19 Jun 2017
Spectral Norm Regularization for Improving the Generalizability of Deep Learning Yuichi Yoshida Takeru Miyato 79 334 0 31 May 2017
Parseval Networks: Improving Robustness to Adversarial Examples Moustapha Cissé Piotr Bojanowski Edouard Grave Yann N. Dauphin Nicolas Usunier AAML 138 807 0 28 Apr 2017
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections Zakaria Mhammedi Andrew D. Hellicar Ashfaqur Rahman James Bailey 87 129 0 01 Dec 2016
Unitary Evolution Recurrent Neural Networks Martín Arjovsky Amar Shah Yoshua Bengio ODL 75 770 0 20 Nov 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 362 19,660 0 09 Mar 2015
Testing the Manifold Hypothesis Charles Fefferman S. Mitter Hariharan Narayanan 151 534 0 01 Oct 2013