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Moment Ambiguity and the Limits of Robust Stochastic Optimization
computer-science-and-game-theorydata-structures-and-algorithmsinformation-theoryoptimization-and-control
We study fundamental information-theoretic limits of robust stochastic optimization when the distribution is known only through its exact moment sequence. We develop a unified framework that produces families of distinct distributions sharing all moments yet inducing radically different optimal deci
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