This introduction to the theory of variational Bayesian learning summarizes recent developments and suggests practical applications.

Variational Bayesian learning is one of the most popular methods in machine learning. Designed for researchers and graduate students in machine learning, this b

Treating VB approximation in signal processing, this monograph is for academic and industrial research groups in signal processing, data analysis, machine learn

The core of this paper is a general set of variational principles for the problems of computing marginal probabilities and modes, applicable to multivariate sta

Sure to be influential, Watanabe's book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular