3 papers
cs.LG2020
To Share or Not To Share: A Comprehensive Appraisal of Weight-Sharing
Aloïs Pourchot, Alexis Ducarouge, Olivier Sigaud
Weight-sharing (WS) has recently emerged as a paradigm to accelerate the automated search for efficient neural architectures, a process dubbed Neural Architecture Search (NAS). Alt…
cs.LG2018
CEM-RL: Combining evolutionary and gradient-based methods for policy search
Aloïs Pourchot, Olivier Sigaud
Deep neuroevolution and deep reinforcement learning (deep RL) algorithms are two popular approaches to policy search. The former is widely applicable and rather stable, but suffers…
cs.LG2018
Importance mixing: Improving sample reuse in evolutionary policy search methods
Aloïs Pourchot, Nicolas Perrin, Olivier Sigaud
Deep neuroevolution, that is evolutionary policy search methods based on deep neural networks, have recently emerged as a competitor to deep reinforcement learning algorithms due t…