Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach. Part II: Theoretical Analysis
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Publication:5143323
DOI10.1137/20M1339842zbMath1457.94011arXiv2008.05793OpenAlexW3100704871MaRDI QIDQ5143323
Valentin De Bortoli, Ana Fernandez Vidal, Marcelo Pereyra, Alain Durmus
Publication date: 11 January 2021
Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2008.05793
stochastic optimizationempirical Bayesimage processinginverse problemsstatistical inferenceMarkov chain Monte Carlo methodsproximal algorithms
Bayesian inference (62F15) Monte Carlo methods (65C05) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
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