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A Simple Method for Convex Optimization in the Oracle Model
[article]
2022
arXiv
pre-print
We give a simple and natural method for computing approximately optimal solutions for minimizing a convex function f over a convex set K given by a separation oracle. Our method utilizes the Frank–Wolfe algorithm over the cone of valid inequalities of K and subgradients of f. Under the assumption that f is L-Lipschitz and that K contains a ball of radius r and is contained inside the origin centered ball of radius R, using O((RL)^2/ε^2·R^2/r^2) iterations and calls to the oracle, our main
arXiv:2011.08557v3
fatcat:vkwiqgbywncn5isbnuuhz2oinu