2 papers
stat.ML2026
Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates
Sanghoon Yu, Min-hwan Oh
We study linear contextual bandits under rare parameter updates: the learner may incorporate reward feedback into its parameter estimate only at a small number of update times, whi…
stat.ML2025
Optimal and Practical Batched Linear Bandit Algorithm
Sanghoon Yu, Min-hwan Oh
We study the linear bandit problem under limited adaptivity, known as the batched linear bandit. While existing approaches can achieve near-optimal regret in theory, they are often…