Learning Filter Functions in Regularisers by Minimising Quotients

DOI10.1007/978-3-319-58771-4_41zbMath1489.68218arXiv1704.00989OpenAlexW2605133707MaRDI QIDQ5864036

Carola-Bibiane Schönlieb, Joana Sarah Grah, Guy Gilboa, Martin Benning

Publication date: 3 June 2022

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1704.00989

zbMATH Keywords

sparse regularisationnonlinear eigenproblemgeneralised inverse power methodregularisation learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Regularity of solutions in optimal control (49N60) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Inverse problems in optimal control (49N45)

Related Items (4)

Wasserstein-Based Projections with Applications to Inverse Problems ⋮ Rayleigh quotient minimization for absolutely one-homogeneous functionals ⋮ Modern regularization methods for inverse problems ⋮ Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks

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