10 citations · 14 across the 10 of their papers we have counts for
3 papers · 1 filter
Survey: Multi-Armed Bandits Meet Large Language Models
Djallel Bouneffouf, Raphael Feraud
Bandit algorithms and Large Language Models (LLMs) have emerged as powerful tools in artificial intelligence, each addressing distinct yet complementary challenges in decision-maki…
Context Attentive Bandits: Contextual Bandit with Restricted Context
Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi +1
We consider a novel formulation of the multi-armed bandit model, which we call the contextual bandit with restricted context, where only a limited number of features can be accesse…
Random Shuffling and Resets for the Non-stationary Stochastic Bandit Problem
Robin Allesiardo, Raphaël Féraud, Odalric-Ambrym Maillard
We consider a non-stationary formulation of the stochastic multi-armed bandit where the rewards are no longer assumed to be identically distributed. For the best-arm identification…