The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
This paper describes a program, called NEWTON, that finds approximate symbolic solutions to parameterized equations in one variable. N E W T O N derives an initial approximation b...
Dynamic plan execution strategies allow an autonomous agent to respond to uncertainties while improving robustness and reducing the need for an overly conservative plan. Executive...
Patrick R. Conrad, Julie A. Shah, Brian C. William...
In this paper we present a multi-GPU parallel volume rendering implemention built using the MapReduce programming model. We give implementation details of the library, including s...
Jeff A. Stuart, Cheng-Kai Chen, Kwan-Liu Ma, John ...