Lifted inference, handling whole sets of indistinguishable objects together, is critical to the effective application of probabilistic relational models to realistic real world ta...
Kristian Kersting, Youssef El Massaoudi, Fabian Ha...
We present in this paper an extension of the messagedriven confidence-driven framework that we developed for onboard guarded software upgrading. The purpose of this work is to pr...
This work deals with the scheduling problem of a directed acyclic graph with interprocessor communication delays. The objective is to minimize the makespan, taking into account the...
A belief-propagation decoder for low-density lattice codes, which represents messages explicitly as a mixture of Gaussians functions, is given. In order to prevent the mixture elem...
In this paper we propose a distributed message-passing algorithm for inference in large scale graphical models. Our method can handle large problems efficiently by distributing a...
Alexander Schwing, Hazan Tamir, Marc Pollefeys, Ra...