160 search results - page 29 / 32 » Any-time probabilistic switching model using bayesian networ... |
99
Voted
NIPS
1998
14 years 11 months ago
1998
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
80
Voted
SECURWARE
2008
IEEE
15 years 4 months ago
2008
IEEE
Abstract. This paper presents our pattern-based approach to run-time requirements monitoring and threat detection being developed as part of an approach to build frameworks support...
94
Voted
GECCO
2004
Springer
15 years 3 months ago
2004
Springer
This paper discusses the performance of a hybrid system which consists of EDP and GP. EDP, Estimation of Distribution Programming, is the program evolution method based on the prob...
120
Voted
CORR
2011
Springer
14 years 2 months ago
2011
Springer
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
79
Voted
BMCBI
2008
14 years 10 months ago
2008
Background: The reconstruction of genetic regulatory networks from microarray gene expression data has been a challenging task in bioinformatics. Various approaches to this proble...