Imad Aouali

On-Policy and Off-Policy Learning for Large Action Spaces

This thesis studies policy learning in interactive systems where an agent observes a context, selects an action from a very large set, and receives partial feedback, and develops structured Bayesian methods for on-policy learning and introduces meTS and dTS, which leverages diffusion-inspired priors to model dependenci...