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Near-Optimal Regret Bounds for Monotone Stochastic Optimization under Semi-Bandit Feedback
Stochastic optimization models sequential decision-making under uncertainty, typically assuming known input distributions. When these distributions are unknown, \citet{agarwal2026semibandit} give an online-to-offline reduction for monotone stochastic optimization under semi-bandit feedback, where on
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