Evolution of Neural Tangent Kernels under Benign and Adversarial
Training

Evolution of Neural Tangent Kernels under Benign and Adversarial Training

21 October 2022

Ramin Hasani

Alexander Amini

Daniela Rus

Papers citing "Evolution of Neural Tangent Kernels under Benign and Adversarial Training"

15 / 15 papers shown

Title
Rethinking Adversarial Training with Neural Tangent Kernel Guanlin Li Han Qiu Shangwei Guo Jiwei Li Tianwei Zhang AAML 12 0 0 04 Dec 2023
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach Shaopeng Fu Di Wang AAML 22 1 0 09 Oct 2023
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning Libin Zhu Chaoyue Liu Adityanarayanan Radhakrishnan M. Belkin 17 13 0 07 Jun 2023
On the Size and Approximation Error of Distilled Sets Alaa Maalouf M. Tukan Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 10 4 0 23 May 2023
How Spurious Features Are Memorized: Precise Analysis for Random and NTK Features Simone Bombari Marco Mondelli AAML 14 4 0 20 May 2023
Dataset Distillation with Convexified Implicit Gradients Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 16 41 0 13 Feb 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels Simone Bombari Shayan Kiyani Marco Mondelli AAML 11 10 0 03 Feb 2023
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation Noel Loo Ramin Hasani Mathias Lechner Alexander Amini Daniela Rus DD 19 5 0 02 Feb 2023
Spectral Evolution and Invariance in Linear-width Neural Networks Zhichao Wang A. Engel Anand D. Sarwate Ioana Dumitriu Tony Chiang 35 7 0 11 Nov 2022
Efficient Dataset Distillation Using Random Feature Approximation Noel Loo Ramin Hasani Alexander Amini Daniela Rus DD 64 95 0 21 Oct 2022
Unadversarial Examples: Designing Objects for Robust Vision Hadi Salman Andrew Ilyas Logan Engstrom Sai H. Vemprala A. Madry Ashish Kapoor WIGM 62 51 0 22 Dec 2020
On The Verification of Neural ODEs with Stochastic Guarantees Sophie Gruenbacher Ramin Hasani Mathias Lechner J. Cyranka S. Smolka Radu Grosu 66 31 0 16 Dec 2020
Geometric compression of invariant manifolds in neural nets J. Paccolat Leonardo Petrini Mario Geiger Kevin Tyloo M. Wyart MLT 39 34 0 22 Jul 2020
TaskNorm: Rethinking Batch Normalization for Meta-Learning J. Bronskill Jonathan Gordon James Requeima Sebastian Nowozin Richard E. Turner 51 89 0 06 Mar 2020
The large learning rate phase of deep learning: the catapult mechanism Aitor Lewkowycz Yasaman Bahri Ethan Dyer Jascha Narain Sohl-Dickstein Guy Gur-Ari ODL 150 198 0 04 Mar 2020