Gassmann HI, Ziemba WT (1986) A tight upper bound for the expectation of a convex function of a multivariate random variable. Prékopa A, Wets RJ-B, eds. Stochastic Programming, 84 Part 1, Mathematical ...

The saddle function results provide a foundation for the sensitivity analysis of primal and dual optimal solutions to general finite-dimensional problems in convex optimization, since such solutions ...

Financial executive pay is a convex function of profits if recipients get a greater increment in pay when returns are high as opposed to moderate, compared with when returns are moderate as opposed to ...

Even without convexity, this algorithm can be generically used as an oracle-efficient optimization algorithm, with accuracy evaluated empirically. We complement our theoretical results with an ...