@inbook{d60d301f15e04e99bc200c90e67d99c7,
title = "On the Importance of α Marginalization in Maximum Entropy",
abstract = "The correct entropic prior, computed by marginalization over the reg- ularization parameter a, is used to invert photoemission data and to restore the famous “Susie” image. Comparison with the conventional maximum entropy procedure shows less overfitting of noise and demonstrates the residual ringing which is intrinsic to ill-posed inversion problems. An improvement to the steepest descent approximation reveals the reason for the overfitting. On top of that, the correct treatment of the regularization parameter is vital for the existence of the continuum-limit of MaxEnt.",
keywords = "Electrical Engineering, Entropic Prior, Image Processing, Inverse Problem, Physics, general, Probability Theory and Stochastic Processes, Regularization, Statistical Physics, Dynamical Systems and Complexity, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics, general",
author = "R. Fischer and Linden, {W. Von Der} and V. Dose",
note = "DOI: 10.1007/978-94-011-5430-727",
year = "1996",
language = "English",
isbn = "978-94-010-6284-8 978-94-011-5430-7",
series = "Fundamental Theories of Physics",
publisher = "Springer Netherlands",
pages = "229--236",
editor = "Hanson, {Kenneth M.} and Silver, {Richard N.}",
booktitle = "Maximum Entropy and Bayesian Methods",
address = "Netherlands",
}