Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
We give a new class of outer bounds on the marginal polytope, and propose a cutting-plane algorithm for efficiently optimizing over these constraints. When combined with a concav...
In this paper we discuss the use of discourse context in spoken dialogue systems and argue that the knowledge of the domain, modelled with the help of dialogue topics is important...
We consider the costs of access to data stored in search trees assuming that those memory accesses are managed with a cache. Our cache memory model is two-level, has a small degre...
The prediction of gene function from genome sequences is one of the main issues in Bioinformatics. Most computational approaches are based on the similarity between sequences to in...