Nearly Minimax-Optimal Regret for Linear Contextual Bandits with Arbitrary Adaptive Action Sets
The upper bound improves the dependence on $K$ by a factor of $K^{1/4}$ and the regret smoothly recovers the $d\sqrt T$ scale once $\log K$ reaches order $d$.
Tian-Yuan Jin
· 0 citations