6 citations · 6 across the 8 of their papers we have counts for
4 papers · 1 filter
Evolution Strategies at the Hyperscale
Bidipta Sarkar, Mattie Fellows, Juan Agustin Duque +17
Evolution Strategies (ES) is a class of powerful black-box optimisation methods that are highly parallelisable and can handle non-differentiable and noisy objectives. However, naïv…
Intent Factored Generation: Unleashing the Diversity in Your Language Model
Eltayeb Ahmed, Uljad Berdica, Martha Elliott +2
Obtaining multiple meaningfully diverse, high quality samples from Large Language Models for a fixed prompt remains an open challenge. Current methods for increasing diversity ofte…
Fully Offline Reinforcement Learning
Mattie Fellows, Clarisse Wibault, Uljad Berdica +3
Offline RL (ORL) promises safe and sample-efficient deployment but existing methods rely on undocumented online interactions for hyperparameter tuning and lack reliable fully offli…
A Clean Slate for Offline Reinforcement Learning
Matthew Thomas Jackson, Uljad Berdica, Jarek Liesen +2
Progress in offline reinforcement learning (RL) has been impeded by ambiguous problem definitions and entangled algorithmic designs, resulting in inconsistent implementations, insu…