1 citations · 1 across the 2 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2024★ 1 cited
Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit
Seok-Jin Kim, Min-hwan Oh
We study the performance guarantees of exploration-free greedy algorithms for the linear contextual bandit problem. We introduce a novel condition, named the \textit{Local Anti-Con…
stat.ML2024
Improved Regret of Linear Ensemble Sampling
Harin Lee, Min-hwan Oh
In this work, we close the fundamental gap of theory and practice by providing an improved regret bound for linear ensemble sampling. We prove that with an ensemble size logarithmi…