Author

Rohan Ghuge

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Oct 2026

Semibandit Learning for Monotone Stochastic Optimization

Firms can improve decisions as data arrive without pausing operations for a separate data-gathering phase, and even with partial, censored, or yes-or-no feedback, the cumulative performance gap grows essentially at the square root rate.

Rohan Ghuge, Zheng-Jia Zhuo, Arpit Agarwal et al. · Operational Research · 2 citations · ⚡1

#machine learning Preprint Oct 2026

Near-Optimal Regret Bounds for Monotone Stochastic Optimization under Semi-Bandit Feedback

A oracle-efficient reduction that combines Bernstein-type optimistic distribution estimates with a Hellinger stability bound for adaptive policy transcripts, aggregating squared marginal errors weighted by the executed policy's probing probabilities.

Tao Hu, Rohan Ghuge · 1 citation