# Distributionally Robust Variance Minimization: Tight Variance Bounds over $f$-Divergence Neighborhoods

@article{Birrell2020DistributionallyRV, title={Distributionally Robust Variance Minimization: Tight Variance Bounds over \$f\$-Divergence Neighborhoods}, author={Jeremiah Birrell}, journal={arXiv: Optimization and Control}, year={2020} }

Distributionally robust optimization (DRO) is a widely used framework for optimizing objective functionals in the presence of both randomness and model-form uncertainty. A key step in the practical solution of many DRO problems is a tractable reformulation of the optimization over the chosen model ambiguity set, which is generally infinite dimensional. Previous works have solved this problem in the case where the objective functional is an expected value. In this paper we study objective…

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