arXiv stat.ML
· Papers
Optimal Regret for Single Index Bandits
arXiv:2605.09454v3 Announce Type: replace Abstract: We study the $textit{single-index bandit}$ problem, where rewards depend on an unknown one-dimensional projection of high-dimensional contexts through an unknown reward function. This model extends linear and generalized linear bandits to a nonparametric setting, and