A fast dual proximal gradient algorithm for convex minimization and applications |
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Authors: | Amir Beck Marc Teboulle |
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Affiliation: | 1. Faculty of Industrial Engineering and Management, Technion - Israel Institute of Technology, Haifa, Israel;2. School of Mathematical Sciences, Tel-Aviv University, Ramat-Aviv, Israel |
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Abstract: | We consider the convex composite problem of minimizing the sum of a strongly convex function and a general extended valued convex function. We present a dual-based proximal gradient scheme for solving this problem. We show that although the rate of convergence of the dual objective function sequence converges to the optimal value with the rate O(1/k2), the rate of convergence of the primal sequence is of the order O(1/k). |
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Keywords: | Dual-based methods Fast gradient methods Convex optimization Rate of convergence |
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