1 citations · 1 across the 6 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
cs.LG2025
Infrequent Exploration in Linear Bandits
Harin Lee, Min-hwan Oh
We study the problem of infrequent exploration in linear bandits, addressing a significant yet overlooked gap between fully adaptive exploratory methods (e.g., UCB and Thompson Sam…
cs.LG2025
Minimax Optimal Reinforcement Learning with Quasi-Optimism
Harin Lee, Min-hwan Oh
In our quest for a reinforcement learning (RL) algorithm that is both practical and provably optimal, we introduce EQO (Exploration via Quasi-Optimism). Unlike existing minimax opt…