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 are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
—In this paper we extend the class of MAP queueing networks to include blocking models, which are useful to describe the performance of service instances which have a limited con...
Vittoria de Nitto Persone, Giuliano Casale, Evgeni...
We report on the design, implementation, and evaluation of a system called Cedar that enables mobile database access with good performance over low-bandwidth networks. This is acc...
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...