Sciweavers

UAI
1996
13 years 6 months ago
A Graph-Theoretic Analysis of Information Value
We derive qualitative relationships about the informationalrelevance of variables in graphical decision models based on a consideration of the topology of the models. Speci cally,...
Kim-Leng Poh, Eric Horvitz
UAI
1996
13 years 6 months ago
Network Engineering for Complex Belief Networks
Developing a large belief network, like any large system, requires systems engineering to manage the design and construction process. We propose that network engineering follow a ...
Suzanne M. Mahoney, Kathryn B. Laskey
UAI
1996
13 years 6 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
UAI
1996
13 years 6 months ago
Efficient Search-Based Inference for noisy-OR Belief Networks: TopEpsilon
Inference algorithms for arbitrary belief networks are impractical for large, complex belief networks. Inference algorithms for specialized classes of belief networks have been sh...
Kurt Huang, Max Henrion
UAI
1996
13 years 6 months ago
Why is diagnosis using belief networks insensitive to imprecision in probabilities?
Recent research has found that diagnostic performance with Bayesian belief networks is often surprisingly insensitive to imprecision in the numerical probabilities. For example, t...
Max Henrion, Malcolm Pradhan, Brendan Del Favero, ...
UAI
1996
13 years 6 months ago
Asymptotic Model Selection for Directed Networks with Hidden Variables
We extend the Bayesian Information Criterion (BIC), an asymptotic approximation for the marginal likelihood, to Bayesian networks with hidden variables. This approximation can be ...
Dan Geiger, David Heckerman, Christopher Meek
UAI
1996
13 years 6 months ago
A Qualitative Markov Assumption and Its Implications for Belief Change
The study of belief change has been an active area in philosophy and AI. In recent years, two special cases of belief change, belief revision and belief update, have been studied ...
Nir Friedman, Joseph Y. Halpern
UAI
1996
13 years 6 months ago
Learning Bayesian Networks with Local Structure
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Nir Friedman, Moisés Goldszmidt
UAI
1996
13 years 6 months ago
An evaluation of structural parameters for probabilistic reasoning: Results on benchmark circuits
Many algorithms for processing probabilistic networks are dependent on the topological properties of the problem's structure. Such algorithmse.g., clustering, conditioning ar...
Yousri El Fattah, Rina Dechter