Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse c...
There is increasing interest within the research community in the design and use of recursive probability models. There remains concern about computational complexity costs and th...
—The StreamIt programming model has been proposed to exploit parallelism in streaming applications on general purpose multicore architectures. This model allows programmers to sp...
Abhishek Udupa, R. Govindarajan, Matthew J. Thazhu...
Variability modelling with feature models is one key technique for specifying the problem space of software product lines (SPLs). To allow for the automatic derivation of a concre...
Abstract— We develop a general framework for MAP estimation in discrete and Gaussian graphical models using Lagrangian relaxation techniques. The key idea is to reformulate an in...
Jason K. Johnson, Dmitry M. Malioutov, Alan S. Wil...