Preprint
Aug 2026
Reoptimization Algorithms for Contextual Bandits with Knapsack Constraints
A natural and simple extension of the Upper-Confidence-Bound (UCB) family of algorithms is proposed and it is shown that by taking advantage of re-optimization, the algorithm achieves an average regret of $O(\frac{(\ln T)^3}{T})$ where $T$ is the horizon length.
Zhen Xu
· 1 citation