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...
The importance estimation problem (estimating the ratio of two probability density functions) has recently gathered a great deal of attention for use in various applications, e.g....
We present a new approach that enables compiler optimization of procedure calls and loop nests containing procedure calls. We introduce two interprocedural transformationsthat mov...
Over the last 25+ years, the software community has been searching for the best models for estimating variables of interest (e.g., cost, defects, and fault proneness). However, li...
In two-way contingency tables analysis, a popular class of models for describing the structure of the association between the two categorical variables are the so-called “associ...