We propose a novel a framework for deriving approximations for intractable probabilistic models. This framework is based on a free energy (negative log marginal likelihood) and ca...
This paper presents an agent strategy for complex bilateral negotiations over many issues with inter-dependent valuations. We use ideas inspired by graph theory and probabilistic ...
Valentin Robu, D. J. A. Somefun, Johannes A. La Po...
In this paper we present a learning based method for vessel segmentation in angiographic videos. Vessel Segmentation is an important task in medical imaging and has been investiga...
One crucial issue in genetic programming (GP) is how to acquire promising building blocks efficiently. In this paper, we propose a GP method (called GPTM, GP with Tree Mining) whi...
Many algorithms for performing inference in graphical models have complexity that is exponential in the treewidth - a parameter of the underlying graph structure. Computing the (m...