We study the problem of projecting a distribution onto (or finding a maximum likelihood distribution among) Markov networks of bounded tree-width. By casting it as the combinatori...
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
Abstract— Particle filters are a frequently used filtering technique in the robotics community. They have been successfully applied to problems such as localization, mapping, o...
Cyrill Stachniss, Giorgio Grisetti, Wolfram Burgar...
We demonstrate that the Linear Multidimensional Assignment Problem with iid random costs is polynomially "-approximable almost surely (a. s.) via a simple greedy heuristic, f...
We consider multi-class blocking systems in which jobs require a single processing step. There are groups of servers that can each serve a different subset of all job classes. The...