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Maximizing a piecewise-linear convex function
Crossposted on Operations Research SE.
I am working on an optimization problem where some of the terms of the objective function to maximize are expressed as a piecewise linear function of variables:
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How does one go from convexity to submodularity?
If I have a function which is convex in the hypercube, $[-1,1]^n$ then when would it imply that its restriction to $\{-1,1\}^n$ is submodular?
It would be helpful is someone can share some specific ...
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