Abstract
Let A and B be two mutually complementary subspaces of a real Hubert space H, T being a maximal monotone operator on H. The method of partial inverses has been introduced by J. Spingarn in 1983 for solving problems in which the object is to find x ∈ A and y ∈ B such that y ∈ Tx. We present a perturbed version of this method and its most important application: a perturbed method of parallel decomposition in convex programming.1
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© 1992 Springer-Verlag Berlin Heidelberg
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Tossings, P. (1992). Mixing proximal regularization, penalization and parallel decomposition in convex programming. In: Oettli, W., Pallaschke, D. (eds) Advances in Optimization. Lecture Notes in Economics and Mathematical Systems, vol 382. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-51682-5_7
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DOI: https://doi.org/10.1007/978-3-642-51682-5_7
Publisher Name: Springer, Berlin, Heidelberg
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