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...
Abstract—The highly stochastic nature of wireless environments makes it desirable to monitor link loss rates in wireless sensor networks. In this paper, we study the loss inferen...
Object-oriented scripting languages like JavaScript and Python are popular partly because of their dynamic features. These include the runtime modification of objects and classes ...
Christopher Anderson, Paola Giannini, Sophia Dross...
Lifted inference algorithms exploit repeated structure in probabilistic models to answer queries efficiently. Previous work such as de Salvo Braz et al.'s first-order variabl...
Brian Milch, Luke S. Zettlemoyer, Kristian Kerstin...
We tackle the general linear instantaneous model (possibly underdetermined and noisy) where we model the source prior with a Student t distribution. The conjugate-exponential char...