BriefGPT.xyz
Jun, 2021
一个胜利的手: 压缩深度网络可以提高对抗分布鲁棒性
A Winning Hand: Compressing Deep Networks Can Improve Out-Of-Distribution Robustness
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James Diffenderfer, Brian R. Bartoldson, Shreya Chaganti, Jize Zhang, Bhavya Kailkhura
TL;DR
文章介绍了一种用Lottery Ticket方法产生紧凑、精确、稳健的神经网络模型的方法,并构建了基于该方法的测试时间集成方法CARD-Decks,在RobustBench上实现了新的最优性能。
Abstract
Two crucial requirements for a successful adoption of
deep learning
(DL) in the wild are: (1)
robustness
to distributional shifts, and (2) model compactness for achieving efficiency. Unfortunately, efforts toward
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