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Accelerated First-Order Methods for Hyperbolic Programming
James Renegar (renegar 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. Keywords: hyperbolic programming, accelerated gradient methods Category 1: Linear, Cone and Semidefinite Programming Category 2: Convex and Nonsmooth Optimization (Convex Optimization ) Citation: arXiv:1512.07569 Download: [PDF] Entry Submitted: 12/23/2015 Modify/Update this entry | ||
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