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Risk Estimators for Choosing Regularization Parameters in Ill-Posed
  Problems - Properties and Limitations
v1v2 (latest)

Risk Estimators for Choosing Regularization Parameters in Ill-Posed Problems - Properties and Limitations

18 January 2017
F. Lucka
K. Proksch
Christoph Brune
N. Bissantz
Martin Burger
Holger Dette
Frank Wübbeling
ArXiv (abs)PDFHTML

Papers citing "Risk Estimators for Choosing Regularization Parameters in Ill-Posed Problems - Properties and Limitations"

3 / 3 papers shown
Title
Discretisation-adaptive regularisation of statistical inverse problems
Discretisation-adaptive regularisation of statistical inverse problems
Tim Jahn
25
3
0
29 Apr 2022
A Probabilistic Oracle Inequality and Quantification of Uncertainty of a
  modified Discrepancy Principle for Statistical Inverse Problems
A Probabilistic Oracle Inequality and Quantification of Uncertainty of a modified Discrepancy Principle for Statistical Inverse Problems
Tim Jahn
16
5
0
25 Feb 2022
Early stopping for statistical inverse problems via truncated SVD
  estimation
Early stopping for statistical inverse problems via truncated SVD estimation
Gilles Blanchard
M. Hoffmann
M. Reiß
62
21
0
19 Oct 2017
1