A Primal-Dual Partial Inverse Algorithm for Constrained Monotone Inclusions: Applications to Stochastic Programming and Mean Field Games

In this work, we study a constrained monotone inclusion involving the normal cone to a closed vector subspace and a priori information on primal solutions. We model this information by imposing that solutions belong to the fixed point set of an averaged nonexpansive mapping. We characterize the solu...

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Veröffentlicht in:	Applied mathematics & optimization Jg. 87; H. 2; S. 21
Hauptverfasser:	Briceño-Arias, Luis, Deride, Julio, López-Rivera, Sergio, Silva, Francisco J.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.04.2023 Springer Nature B.V Springer Verlag (Germany)
Schlagworte:	Algorithms Applied mathematics Calculus of Variations and Optimal Control; Optimization Control Convex analysis Couplings Efficiency Equilibrium Games Hilbert space Inclusions Mathematical and Computational Physics Mathematical Methods in Physics Mathematics Mathematics and Statistics Methods Numerical and Computational Physics Optimization Partial differential equations Simulation Stochastic programming Systems Theory Theoretical Traffic assignment 65K15 65K05 Constrained LASSO 91-08 Stochastic arc capacity expansion Monotone operator theory 90C25 Partial inverse method Constrained convex optimization 90C90 Primal-dual splitting Mean field games 47H05
ISSN:	0095-4616, 1432-0606
Online-Zugang:	Volltext
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