22 citations · 24 across the 4 of their papers we have counts for
4 papers · 1 filter
On numerical approximation schemes for expectation propagation
Alexis Roche
Several numerical approximation strategies for the expectation-propagation algorithm are studied in the context of large-scale learning: the Laplace method, a faster variant of it,…
Composite Bayesian inference
Alexis Roche
We revisit and generalize the concept of composite likelihood as a method to make a probabilistic inference by aggregation of multiple Bayesian agents, thereby defining a class of…
Approximate inference via variational sampling
Alexis Roche
A new method called "variational sampling" is proposed to estimate integrals under probability distributions that can be evaluated up to a normalizing constant. The key idea is to…
EM algorithm and variants: an informal tutorial
Alexis Roche
The expectation-maximization (EM) algorithm introduced by Dempster et al in 1977 is a very general method to solve maximum likelihood estimation problems. In this informal report,…