2 papers
cs.LG2022★ 3 cited
Bayesian Generational Population-Based Training
Xingchen Wan, Cong Lu, Jack Parker-Holder +4
Reinforcement learning (RL) offers the potential for training generally capable agents that can interact autonomously in the real world. However, one key limitation is the brittlen…
cs.LG2021
DARTS without a Validation Set: Optimizing the Marginal Likelihood
Miroslav Fil, Binxin Ru, Clare Lyle +1
The success of neural architecture search (NAS) has historically been limited by excessive compute requirements. While modern weight-sharing NAS methods such as DARTS are able to f…