Geometric measures of convex sets and bounds on problem sensitivity and robustness for conic linear optimization

The effect of data perturbation and uncertainty has always been an important consideration in Optimization. It is important to know whether a given problem is very sensible to perturbations on the data or, on the contrary, is more “robust”. Problem geometry does have an impact on the sensitivity of...

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