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Proximal algorithms for constrained composite optimization, with applications to solving low-rank SDPs.
arXiv: Optimization and Control, (2019)
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Abstract
We study a family of (potentially non-convex) constrained optimization problems with convex composite structure. Through a novel analysis of non-smooth geometry, we show that proximal-type algorithms applied to exact penalty formulations of such problems exhibit local linear convergence under a quadratic growth condition, which the compos...More
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