Stochastic gradient descent for linear inverse problems in Hilbert spaces

DOI10.1090/mcom/3714zbMath1504.47027OpenAlexW4200434021MaRDI QIDQ5082036

Shuai Lu, Peter Mathé

Publication date: 15 June 2022

Published in: Mathematics of Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1090/mcom/3714

zbMATH Keywords

Landweber iterationstochastic gradient descentill-posed operator equationsregularization schemes

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Monte Carlo methods (65C05) Linear operators and ill-posed problems, regularization (47A52)

Related Items (4)

Stochastic asymptotical regularization for linear inverse problems ⋮ Stochastic mirror descent method for linear ill-posed problems in Banach spaces ⋮ Stochastic linear regularization methods: random discrepancy principle and applications ⋮ On the Convergence of Stochastic Gradient Descent for Linear Inverse Problems in Banach Spaces

Uses Software

• Regularization tools

Cites Work

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