Search results for " 65K10"

showing 5 items of 5 documents

A product space reformulation with reduced dimension for splitting algorithms

2021

AbstractIn this paper we propose a product space reformulation to transform monotone inclusions described by finitely many operators on a Hilbert space into equivalent two-operator problems. Our approach relies on Pierra’s classical reformulation with a different decomposition, which results in a reduction of the dimension of the outcoming product Hilbert space. We discuss the case of not necessarily convex feasibility and best approximation problems. By applying existing splitting methods to the proposed reformulation we obtain new parallel variants of them with a reduction in the number of variables. The convergence of the new algorithms is straightforwardly derived with no further assump…

Control and OptimizationApplied Mathematicsdouglas – rachford algorithm47H05 47J25 49M27 65K10 90C30UNESCO::CIENCIAS TECNOLÓGICASComputational MathematicsOptimization and Control (math.OC)splitting algorithmprojection methodsFOS: Mathematicspierra’s product space reformulationmonotone inclusionsMathematics - Optimization and Controlfeasibility problemComputational Optimization and Applications
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CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration

2017

International audience; In this paper, we propose a new framework to remove parts of the systematic errors affecting popular restoration algorithms, with a special focus for image processing tasks. Generalizing ideas that emerged for $\ell_1$ regularization, we develop an approach re-fitting the results of standard methods towards the input data. Total variation regularizations and non-local means are special cases of interest. We identify important covariant information that should be preserved by the re-fitting method, and emphasize the importance of preserving the Jacobian (w.r.t. the observed signal) of the original estimator. Then, we provide an approach that has a ``twicing'' flavor a…

FOS: Computer and information sciencesInverse problemsMathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer Vision and Pattern Recognition (cs.CV)General MathematicsComputer Science - Computer Vision and Pattern RecognitionMachine Learning (stat.ML)Mathematics - Statistics TheoryImage processingStatistics Theory (math.ST)02 engineering and technologyDebiasing[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural sciencesRegularization (mathematics)Boosting010104 statistics & probabilitysymbols.namesake[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Variational methods[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Statistics - Machine LearningRefittingMSC: 49N45 65K10 68U10[ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingFOS: Mathematics0202 electrical engineering electronic engineering information engineeringCovariant transformation[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicsImage restoration[ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML]MathematicsApplied Mathematics[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]EstimatorInverse problem[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Jacobian matrix and determinantsymbolsTwicing020201 artificial intelligence & image processingAffine transformationAlgorithm
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Regularity of sets under a reformulation in a product space of reduced dimension

2023

Different notions on regularity of sets and of collection of sets play an important role in the analysis of the convergence of projection algorithms in nonconvex scenarios. While some projection algorithms can be applied to feasibility problems defined by finitely many sets, some other require the use of a product space reformulation to construct equivalent problems with two sets. In this work we analyze how some regularity properties are preserved under a reformulation in a product space of reduced dimension. This allows us to establish local linear convergence of parallel projection methods which are constructed through this reformulation.

Optimization and Control (math.OC)FOS: Mathematics47H05 47J25 49M27 65K10 90C30Mathematics - Optimization and Control
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Guaranteed lower bounds for cost functionals of time-periodic parabolic optimization problems

2019

In this paper, a new technique is shown for deriving computable, guaranteed lower bounds of functional type (minorants) for two different cost functionals subject to a parabolic time-periodic boundary value problem. Together with previous results on upper bounds (majorants) for one of the cost functionals, both minorants and majorants lead to two-sided estimates of functional type for the optimal control problem. Both upper and lower bounds are derived for the second new cost functional subject to the same parabolic PDE-constraints, but where the target is a desired gradient. The time-periodic optimal control problems are discretized by the multiharmonic finite element method leading to lar…

Optimization problemtime-periodic conditionmultiharmonic finite element methodDiscretizationtwo-sided boundsSystems and Control (eess.SY)010103 numerical & computational mathematicsSystem of linear equationsElectrical Engineering and Systems Science - Systems and Control01 natural sciencesUpper and lower boundsSaddle pointFOS: MathematicsFOS: Electrical engineering electronic engineering information engineeringApplied mathematicsMathematics - Numerical AnalysisBoundary value problem0101 mathematicsMathematics - Optimization and ControlMathematicsosittaisdifferentiaaliyhtälöt35Kxx 65M60 65M70 65M15 65K10parabolic optimal control problemsNumerical Analysis (math.NA)matemaattinen optimointiOptimal controlFinite element method010101 applied mathematicsComputational MathematicsComputational Theory and MathematicsOptimization and Control (math.OC)Modeling and Simulationa posteriori error analysisnumeerinen analyysiguaranteed lower boundsComputers & Mathematics with Applications
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Weak and strong convergence of an inertial proximal method for solving bilevel monotone equilibrium problems

2022

In this paper, we introduce an inertial proximal method for solving a bilevel problem involving two monotone equilibrium bifunctions in Hilbert spaces. Under suitable conditions and without any restrictive assumption on the trajectories, the weak and strong convergence of the sequence generated by the iterative method are established. Two particular cases illustrating the proposed method are thereafter discussed with respect to hierarchical minimization problems and equilibrium problems under saddle point constraint. Furthermore, a numerical example is given to demonstrate the implementability of our algorithm. The algorithm and its convergence results improve and develop previous results i…

Weak and strong convergenceBilevel Equilibrium problemsOptimization and Control (math.OC)G.1.6Equilibrium Fitzpatrick transformFOS: MathematicsProximal algorithm90C33 49J40 46N10 65K15 65K10[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Monotone bifunctionsMathematics - Optimization and Control
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