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About this paper
Meiyi Zhu, Osvaldo Simeone
The authors design quantum measurements for decision-making under optimized certainty equivalent (OCE) risk objectives, including conditional value at risk (CVaR). For piecewise-linear gains, they reduce optimization to at most K|S||A| reserve candidates, each requiring a semidefinite program. In one simulated four-state ensemble, CVaR optimization improves the lower-tail utility distribution relative to average-utility optimization, but lowers mean utility.
Summary by alphaXiv.
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