A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
In most enterprises, databases are deployed on dedicated database servers. Often, these servers are underutilized much of the time. For example, in traces from almost 200 producti...
Carlo Curino, Evan P. C. Jones, Samuel Madden, Har...
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...
Positive results from new object-oriented tools for scientific programming are reported. Using template classes, abstractions of matrix representations are available that subsume...
Peter Gottschling, David S. Wise, Michael D. Adams