To Share or Not To Share: A Comprehensive Appraisal of Weight-Sharing

1 code implementation • 11 Feb 2020 • 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).

Neural Architecture Search

CEM-RL: Combining evolutionary and gradient-based methods for policy search

2 code implementations • 2 Oct 2018 • Aloïs Pourchot, Olivier Sigaud

In this paper, we propose a different combination scheme using the simple cross-entropy method (CEM) and Twin Delayed Deep Deterministic policy gradient (td3), another off-policy deep RL algorithm which improves over ddpg.

Importance mixing: Improving sample reuse in evolutionary policy search methods

no code implementations • 17 Aug 2018 • Aloïs Pourchot, Nicolas Perrin, Olivier Sigaud

Then, from an empirical comparison based on a simple benchmark, we show that, though it actually provides better sample efficiency, it is still far from the sample efficiency of deep reinforcement learning, though it is more stable.

reinforcement-learning Reinforcement Learning (RL)