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Sep, 2021
机器学习安全中尚未解决的问题
Unsolved Problems in ML Safety
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Dan Hendrycks, Nicholas Carlini, John Schulman, Jacob Steinhardt
TL;DR
通过提出四个安全性问题:鲁棒性、监控风险、降低内在模型风险和降低系统风险,本篇研究为机器学习的安全性提供了新的技术路线和解决方案。
Abstract
machine learning
(ML) systems are rapidly increasing in size, are acquiring new capabilities, and are increasingly deployed in high-stakes settings. As with other powerful technologies,
safety
for ML should be a
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