In this article we address the issue of denoising photon-limited image data by deriving new and efficient multivariate Bayesian estimators that approximate the conditional expecta...
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
Resource discovery in a distributed digital library poses many challenges, one of which is how to choose search engines for query distribution, given a query and a set of search e...
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...
One of the keys for the success of parallel processing is the availability of high-level programming languages for on-the-shelf parallel architectures. Using explicit message passi...