Comparison of formulations and solution methods for image restoration problems

DOI10.1088/0266-5611/17/6/326zbMath1016.94004OpenAlexW2068099534WikidataQ110030199 ScholiaQ110030199MaRDI QIDQ2774155

Marko M. Mäkelä, K. Majava, Tommi Kärkkäinen

Publication date: 11 June 2002

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/5d32a83de27e0259adc1ca9f466a32bd0b736ef1

zbMATH Keywords

nonsmooth optimizationconjugate gradient methodproximal bundle methodimage restorationbundle-Newton method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Nonsmooth analysis (49J52) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

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MLP in Layer-Wise Form with Applications to Weight Decay ⋮ New limited memory bundle method for large-scale nonsmooth optimization ⋮ Robust Formulations for Training Multilayer Perceptrons ⋮ Globally convergent limited memory bundle method for large-scale nonsmooth optimization ⋮ Dualization of signal recovery problems ⋮ TV‐like regularization for backward parabolic problems ⋮ A modified nonlinear conjugate gradient algorithm for large-scale nonsmooth convex optimization ⋮ Adaptive limited memory bundle method for bound constrained large-scale nonsmooth optimization ⋮ A modified Hestenes and Stiefel conjugate gradient algorithm for large-scale nonsmooth minimizations and nonlinear equations

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