LAUSR

Learning Convex Regularizers for Optimal Bayesian Denoising

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0 Published in 2018 at "IEEE Transactions on Signal Processing"

DOI: 10.1109/tsp.2017.2777407

Abstract: We propose a data-driven algorithm for the Bayesian estimation of stochastic processes from noisy observations. The primary statistical properties of the sought signal are specified by the penalty function (i.e., negative logarithm of the prior… read more here.

Keywords: optimal bayesian; penalty function; learning convex; convex regularizers ... See more keywords