Ill-Posed Nonlinear Optimization Problems and Uniform Accuracy Estimates of Regularization Methods

DOI10.1080/01630563.2020.1845729zbMath1461.49018OpenAlexW3106977310MaRDI QIDQ4985165

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Publication date: 22 April 2021

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630563.2020.1845729

zbMATH Keywords

convex setMinkowski functionalregularizing operatorstrong convexityaccuracy estimateweakly lower semicontinuous functionalill-posed optimization problemerror level

Mathematics Subject Classification ID

Methods involving semicontinuity and convergence; relaxation (49J45) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20)

Cites Work

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• Reduction of variational inequalities with irregular operators on a ball to regular operator equations
• Regularization methods in Banach spaces.
• Stable approximation schemes for ill-posed convex variational problems
• On possibility of obtaining linear accuracy evaluation of approximate solutions to inverse problems
• Inverse Problems
• Nonlinear Ill-posed Problems of Monotone Type
• On a characteristic property of conditionally well-posed problems
• Conditionally well-posed and generalized well-posed problems

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