Efficient Adversarial Training With Data Pruning

1 July 2022

Papers citing "Efficient Adversarial Training With Data Pruning"

5 / 5 papers shown

Title
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning Patrik Okanovic R. Waleffe Vasilis Mageirakos Konstantinos E. Nikolakakis Amin Karbasi Dionysis Kalogerias Nezihe Merve Gürel Theodoros Rekatsinas DD 45 12 0 28 May 2023
Less is More: Data Pruning for Faster Adversarial Training Yize Li Pu Zhao X. Lin B. Kailkhura Ryan Goldh AAML 15 9 0 23 Feb 2023
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 186 273 0 28 Sep 2021
Understanding the Error in Evaluating Adversarial Robustness Pengfei Xia Ziqiang Li Hongjing Niu Bin Li AAML ELM 34 5 0 07 Jan 2021
Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression Nilaksh Das Madhuri Shanbhogue Shang-Tse Chen Fred Hohman Siwei Li Li-Wei Chen Michael E. Kounavis Duen Horng Chau FedML AAML 43 224 0 19 Feb 2018