8 citations · 17 across the 6 of their papers we have counts for
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cs.LG2020★ 3 cited
EVO-RL: Evolutionary-Driven Reinforcement Learning
Ahmed Hallawa, Thorsten Born, Anke Schmeink +6
In this work, we propose a novel approach for reinforcement learning driven by evolutionary computation. Our algorithm, dubbed as Evolutionary-Driven Reinforcement Learning (evo-RL…
cs.LG2019
Automated design of error-resilient and hardware-efficient deep neural networks
Christoph Schorn, Thomas Elsken, Sebastian Vogel +3
Applying deep neural networks (DNNs) in mobile and safety-critical systems, such as autonomous vehicles, demands a reliable and efficient execution on hardware. Optimized dedicated…