Lipschitz Constant Meets Condition Number: Learning Robust and Compact Deep Neural Networks

Lipschitz Constant Meets Condition Number: Learning Robust and Compact Deep Neural Networks

26 March 2025

Papers citing "Lipschitz Constant Meets Condition Number: Learning Robust and Compact Deep Neural Networks"

15 / 15 papers shown

Title
SORSA: Singular Values and Orthonormal Regularized Singular Vectors Adaptation of Large Language Models Yang Cao 86 2 0 21 Aug 2024
Structured Pruning for Deep Convolutional Neural Networks: A survey Yang He Lingao Xiao 3DPC 80 137 0 01 Mar 2023
A Universal Law of Robustness via Isoperimetry Sébastien Bubeck Mark Sellke 39 218 0 26 May 2021
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 216 1,846 0 03 Mar 2020
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 85 987 0 29 Nov 2019
Model Compression with Adversarial Robustness: A Unified Optimization Framework Shupeng Gui Haotao Wang Chen Yu Haichuan Yang Zhangyang Wang Ji Liu MQ 47 138 0 10 Feb 2019
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 102 1,781 0 30 May 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 83 467 0 31 Jan 2018
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 157 2,151 0 21 Aug 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
Soft Weight-Sharing for Neural Network Compression Karen Ullrich Edward Meeds Max Welling 167 417 0 13 Feb 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 264 8,552 0 16 Aug 2016
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 257 8,842 0 01 Oct 2015
Learning both Weights and Connections for Efficient Neural Networks Song Han Jeff Pool J. Tran W. Dally CVBM 310 6,681 0 08 Jun 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014