Kullback proximal algorithms for maximum-likelihood estimation

DOI10.1109/18.857792zbMath1021.68101arXiv1201.5907OpenAlexW2145302655MaRDI QIDQ2705920

Alfred O. III Hero, Stéphane Chrétien

Publication date: 19 March 2001

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1201.5907

zbMATH Keywords

Kullback-Leibler divergenceexpectation-maximization algorithmproximal point algorithmemission tomographymaximum-likelihood image reconstruction

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Biomedical imaging and signal processing (92C55) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) General topics in the theory of algorithms (68W01)

Related Items (8)

Analysis of a generalised expectation–maximisation algorithm for Gaussian mixture models: a control systems perspective ⋮ Statistical estimation of delays in a multicast tree using accelerated EM ⋮ Space alternating penalized Kullback proximal point algorithms for maximizing likelihood with nondifferentiable penalty ⋮ Multivariate Myriad Filters Based on Parameter Estimation of Student-$t$ Distributions ⋮ On EM algorithms and their proximal generalizations ⋮ Proximal algorithms in statistics and machine learning ⋮ Sparse mixture models inspired by ANOVA decompositions ⋮ PCA reduced Gaussian mixture models with applications in superresolution

Uses Software

• L-BFGS

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