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...
The Replica Placement Problem (RPP) aims at creating a set of duplicated data objects across the nodes of a distributed system in order to optimize certain criteria. Typically, RP...
Thanasis Loukopoulos, Petros Lampsas, Ishfaq Ahmad
We consider the important problem of energy balanced data propagation in wireless sensor networks and we extend and generalize previous works by allowing adaptive energy assignment...
— Multi-agent coordination problems can be cast as distributed optimization tasks. Probability Collectives (PCs) are techniques that deal with such problems in discrete and conti...
In the present study, an efficient strategy for retrieving texture images from large texture databases is introduced and studied within a distributional-statistical framework. Our...
Vasileios K. Pothos, Christos Theoharatos, George ...