A new framework for multi-parameter regularization
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Publication:329016
DOI10.1007/s10543-015-0595-4zbMath1353.65032OpenAlexW2301878071MaRDI QIDQ329016
Silvia Gazzola, Lothar Reichel
Publication date: 21 October 2016
Published in: BIT (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10543-015-0595-4
Ill-posedness and regularization problems in numerical linear algebra (65F22) Iterative numerical methods for linear systems (65F10)
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Uses Software
Cites Work
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- Multi-parameter Tikhonov regularization
- Discrete ill-posed least-squares problems with a solution norm constraint
- Tikhonov regularization based on generalized Krylov subspace methods
- Multi-parameter regularization and its numerical realization
- An iterative method for Tikhonov regularization with a general linear regularization operator
- Simple square smoothing regularization operators
- Matrix decompositions for Tikhonov regularization
- Arnoldi-Tikhonov regularization methods
- Regularization tools: A Matlab package for analysis and solution of discrete ill-posed problems
- Multi-parameter regularization techniques for ill-conditioned linear systems
- Tikhonov regularization and the L-curve for large discrete ill-posed problems
- Iterative methods for image deblurring: A Matlab object-oriented approach
- On Krylov projection methods and Tikhonov regularization
- Combining approximate solutions for linear discrete ill-posed problems
- Discontinuous parameter estimates with least squares estimators
- Convergence analysis of minimization-based noise level-free parameter choice rules for linear ill-posed problems
- Multi-parameter Arnoldi-Tikhonov methods
- Orthogonal projection regularization operators
- Two-parameter discrepancy principle for combined projection and Tikhonov regularization of ill-posed problems
- A Bilevel Optimization Approach for Parameter Learning in Variational Models
- Discrepancy curves for multi-parameter regularization
- Parameter Choice Strategies for Multipenalty Regularization
- Embedded techniques for choosing the parameter in Tikhonov regularization
- Efficient determination of multiple regularization parameters in a generalized L-curve framework
- Deblurring Images
- Rank-Deficient and Discrete Ill-Posed Problems
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