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Zhong Han

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#machine learning Preprint Nov 2026

Regret without Optimal-Arm Feedback under Reward-Dependent Delays

We study stochastic bandits with reward-dependent delays, possibly infinite, whose reports omit the originating round. For each $c\in[0,1)$, Balanced Historical Optimism (BHO) has a delay term controlled by the largest suboptimal-arm quantile at level $1-c\Delta_i$, without requiring optimal-arm reports. Lower bounds g...

Zhong Han · 0 citations