# Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization

@article{Rangan2015InferenceFG,
title={Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization},
author={S. Rangan and A. Fletcher and Philip Schniter and Ulugbek S. Kamilov},
journal={IEEE Transactions on Information Theory},
year={2015},
volume={63},
pages={676-697}
}
• S. Rangan, +1 author Ulugbek S. Kamilov
• Published 2015
• Computer Science, Mathematics
• IEEE Transactions on Information Theory
• Generalized linear models, where a random vector x is observed through a noisy, possibly nonlinear, function of a linear transform $\mathrm {z}= \mathrm {A} \mathrm {x}$ , arise in a range of applications in nonlinear filtering and regression. Approximate message passing (AMP) methods, based on loopy belief propagation, are a promising class of approaches for approximate inference in these models. AMP methods are computationally simple, general, and admit precise analyses with testable… CONTINUE READING