Qijia He

Learning Across the Gap: Hybrid Multi-armed Bandits with Heterogeneous Offline and Online Data

The multi-armed bandit (MAB) is a fundamental online decision-making framework that has been extensively studied over the past two decades. To mitigate the high cost and slow convergence of purely online learning, modern MAB approaches have explored _hybrid_ paradigms that leverage offline data to w…