Uncertainty in Artificial Intelligence
First Name   Last Name   Password   Forgot Password   Log in!
    Proceedings   Proceeding details   Article details         Authors         Search    
A Scheme for Approximating Probabilistic Inference
Rina Dechter, Irina Rish
Abstract:
This paper describes a class of probabilistic approximation algorithms based on bucket elimination which offer adjustable levels of accuracy and efficiency. We analyze the approximation for several tasks: finding the most probable explanation, belief updating and finding the maximum a posteriori hypothesis. We identify regions of completeness and provide preliminary empirical evaluation on randomly generated networks.
Keywords:
Pages: 132-141
PS Link:
PDF Link: /papers/97/p132-dechter.pdf
BibTex:
@INPROCEEDINGS{Dechter97,
AUTHOR = "Rina Dechter and Irina Rish",
TITLE = "A Scheme for Approximating Probabilistic Inference",
BOOKTITLE = "Proceedings of the Thirteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-97)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1997",
PAGES = "132--141"
}


hosted by DSL   •   site info   •   help