Maximum a posteriori (MAP) inference in Markov Random Fields (MRFs) is an NP-hard problem, and thus research has focussed on either finding efficiently solvable subclasses (e.g. t...
Dhruv Batra, Andrew Gallagher, Devi Parikh, Tsuhan...
We consider the variant of the minimum vertex cover problem in which we require that the cover induces a connected subgraph. We give new approximation results for this problem in d...
Abstract— The performance of the widely applied timedomain channel estimation for SISO- and MIMO-OFDM systems strongly depends on the preciseness of information regarding maximum...
Marco Krondorf, Ting-Jung Liang, M. Goblirsch, Ger...
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model ...
We study the lower-bounded facility location problem, which generalizes the classical uncapacitated facility location problem in that it comes with lower bound constraints for the...