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- W2078665452 abstract "The aim of this paper is to develop an efficient algorithm for solving a class of unconstrained nondifferentiable convex optimization problems in finite dimensional spaces. To this end we formulate first its Fenchel dual problem and regularize it in two steps into a differentiable strongly convex one with Lipschitz continuous gradient. The doubly regularized dual problem is then solved via a fast gradient method with the aim of accelerating the resulting convergence scheme. The theoretical results are finally applied to an l 1 regularization problem arising in image processing." @default.
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- W2078665452 date "2012-12-13" @default.
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- W2078665452 title "A double smoothing technique for solving unconstrained nondifferentiable convex optimization problems" @default.
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- W2078665452 doi "https://doi.org/10.1007/s10589-012-9523-6" @default.
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