most citedOn the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method

14 citations · 15 across the 2 of their papers we have counts for

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cs.AI2020

Verifiably Safe Exploration for End-to-End Reinforcement Learning

Nathan Hunt, Nathan Fulton, Sara Magliacane +3

Deploying deep reinforcement learning in safety-critical settings requires developing algorithms that obey hard constraints during exploration. This paper contributes a first appro…