3 papers
cs.LG2025
PAC Apprenticeship Learning with Bayesian Active Inverse Reinforcement Learning
Ondrej Bajgar, Dewi S. W. Gould, Jonathon Liu +3
As AI systems become increasingly autonomous, reliably aligning their decision-making with human preferences is essential. Inverse reinforcement learning (IRL) offers a promising a…
cs.LG2024
Toward Information Theoretic Active Inverse Reinforcement Learning
Ondrej Bajgar, Sid William Gould, Rohan Narayan Langford Mitta +3
As AI systems become increasingly autonomous, aligning their decision-making to human preferences is essential. In domains like autonomous driving or robotics, it is impossible to…
cs.LG2024
On the Anatomy of Attention
Nikhil Khatri, Tuomas Laakkonen, Jonathon Liu +1
We introduce a category-theoretic diagrammatic formalism in order to systematically relate and reason about machine learning models. Our diagrams present architectures intuitively…