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UAI
1998
15 years 1 months ago
Context-specific approximation in probabilistic inference
There is evidence that the numbers in probabilistic inference don't really matter. This paper considers the idea that we can make a probabilistic model simpler by making fewe...
David Poole
98
Voted
UAI
1997
15 years 1 months ago
Robustness Analysis of Bayesian Networks with Local Convex Sets of Distributions
Robust Bayesian inference is the calculation of posterior probability bounds given perturbations in a probabilistic model. This paper focuses on perturbations that can be expresse...
Fabio Gagliardi Cozman
107
Voted
AAAI
2008
15 years 2 months ago
Revising Imprecise Probabilistic Beliefs in the Framework of Probabilistic Logic Programming
Probabilistic logic programming is a powerful technique to represent and reason with imprecise probabilistic knowledge. A probabilistic logic program (PLP) is a knowledge base whi...
Anbu Yue, Weiru Liu
NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 3 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
AI
2006
Springer
15 years 3 months ago
An Improved LAZY-AR Approach to Bayesian Network Inference
We propose LAZY arc-reversal with variable elimination (LAZY-ARVE) as a new approach to probabilistic inference in Bayesian networks (BNs). LAZY-ARVE is an improvement upon LAZY ar...
Cory J. Butz, Shan Hua