56 search results - page 2 / 12 » Approximation of Data by Decomposable Belief Models |
UAI
2000
13 years 6 months ago
2000
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tracta...
UAI
1997
13 years 6 months ago
1997
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
IJAR
2008
13 years 5 months ago
2008
This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contai...
AAAI
2006
13 years 6 months ago
2006
As embedded systems grow increasingly complex, there is a pressing need for diagnosing and monitoring capabilities that estimate the system state robustly. This paper is based on ...