A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
This paper investigates methods that balance time and space constraints against the quality of Bayesian network inferences--we explore the three-dimensional spectrum of "time · space · quality" trade-offs. The main result of our investigation is the adaptive conditioning algorithm, an inference algorithm that works by dividing a Bayesian network into sub-networks and processing each sub-network with a combination of exact and anytime strategies. The algorithm seeks a balanced synthesis ofdoi:10.1016/j.ijar.2004.04.001 fatcat:lrvtscaumvbuhny56scwycpn4e