Interior-Point Lagrangian Decomposition Method for Separable Convex Optimization |
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Authors: | I Necoara J A K Suykens |
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Institution: | 1.Automatic Control and Systems Engineering Department,University Politehnica Bucharest,Bucharest,Romania;2.Department of Electrical Engineering (ESAT),Katholieke Universiteit Leuven,Leuven–Heverlee,Belgium |
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Abstract: | In this paper, we propose a distributed algorithm for solving large-scale separable convex problems using Lagrangian dual
decomposition and the interior-point framework. By adding self-concordant barrier terms to the ordinary Lagrangian, we prove
under mild assumptions that the corresponding family of augmented dual functions is self-concordant. This makes it possible
to efficiently use the Newton method for tracing the central path. We show that the new algorithm is globally convergent and
highly parallelizable and thus it is suitable for solving large-scale separable convex problems. |
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