Accelerated First-Order Methods for Hyperbolic Programming
Optimization and Control
2017-05-30 v3
Abstract
A framework is developed for applying accelerated methods to general hyperbolic programming, including linear, second-order cone, and semidefinite programming as special cases. The approach replaces a hyperbolic program with a convex optimization problem whose smooth objective function is explicit, and for which the only constraints are linear equations (one more linear equation than for the original problem). Virtually any first-order method can be applied. Iteration bounds for a representative accelerated method are derived.
Cite
@article{arxiv.1512.07569,
title = {Accelerated First-Order Methods for Hyperbolic Programming},
author = {James Renegar},
journal= {arXiv preprint arXiv:1512.07569},
year = {2017}
}
Comments
A (serious) typo in specifying the main algorithm has been corrected, and suggestions made by referees have been addressed (submitted to Mathematical Programming)