5 citations · 8 across the 3 of their papers we have counts for
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cs.LG2022★ 5 cited
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars
Simon Schrodi, Danny Stoll, Binxin Ru +3
The discovery of neural architectures from simple building blocks is a long-standing goal of Neural Architecture Search (NAS). Hierarchical search spaces are a promising step towar…
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…