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arxiv: 1805.09396 · v1 · pith:BYB7COVDnew · submitted 2018-05-23 · 🧮 math.OC · cs.NA· math.NA

Douglas-Rachford splitting for a Lipschitz continuous and a strongly monotone operator

classification 🧮 math.OC cs.NAmath.NA
keywords monotoneoperatoroperatorscontinuousconvergencedouglas-rachfordlinearlipschitz
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The Douglas-Rachford method is a popular splitting technique for finding a zero of the sum of two subdifferential operators of proper closed convex functions; more generally two maximally monotone operators. Recent results concerned with linear rates of convergence of the method require additional properties of the underlying monotone operators, such as strong monotonicity and cocoercivity. In this paper, we study the case when one operator is Lipschitz continuous but not necessarily a subdifferential operator and the other operator is strongly monotone. This situation arises in optimization methods which involve primal-dual approaches. We provide new linear convergence results in this setting.

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    Douglas-Rachford splitting applied to affine VIs from linear-quadratic dynamic games yields linear convergence and local closed-form solutions near the attractor.