Assaf Zeevi

Recurrent non-stationarity unlocks data reuse, but its "safe" application hinges on a bias-variance tradeoff akin to classical settings, with a novel algorithm achieving near-optimal regret.

Instance-optimality in MNL-based RL is now achievable, thanks to a new algorithm that adapts to the variance of learner-environment interactions.