3 papers
stat.ML2025
DataRater: Meta-Learned Dataset Curation
Dan A. Calian, Gregory Farquhar, Iurii Kemaev +9
The quality of foundation models depends heavily on their training data. Consequently, great efforts have been put into dataset curation. Yet most approaches rely on manual tuning…
cs.LG2025
Scalable Meta-Learning via Mixed-Mode Differentiation
Iurii Kemaev, Dan A Calian, Luisa M Zintgraf +2
Gradient-based bilevel optimisation is a powerful technique with applications in hyperparameter optimisation, task adaptation, algorithm discovery, meta-learning more broadly, and…
cs.LG2025
A Tutorial on Meta-Reinforcement Learning
Jacob Beck, Risto Vuorio, Evan Zheran Liu +4
While deep reinforcement learning (RL) has fueled multiple high-profile successes in machine learning, it is held back from more widespread adoption by its often poor data efficien…