A comment on the "A unified Bayesian inference framework for generalized linear models"
Abstract
The recent work `A unified Bayesian inference framework for generalized linear models' meng1 shows that the GLM can be solved via iterating between the standard linear module (SLM) (running with standard Bayesian algorithm) and the minimum mean squared error (MMSE) module. The proposed framework utilizes expectation propagation and corresponds to the sum-product version Rangan1. While in Rangan1, a max-sum GAMP is also proposed. What is their intrinsic relationship? This comment aims to answer this.
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