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ICGI
1994
Springer
15 years 1 months ago
Inducing Probabilistic Grammars by Bayesian Model Merging
We describe a framework for inducing probabilistic grammars from corpora of positive samples. First, samples are incorporated by adding ad-hoc rules to a working grammar; subseque...
Andreas Stolcke, Stephen M. Omohundro
JCIT
2010
174views more  JCIT 2010»
14 years 4 months ago
Efficient Ming of Top-K Closed Sequences
Sequence mining is an important data mining task. In order to retrieve interesting sequences from a large database, a minimum support threshold is needed to be specified. Unfortun...
Panida Songram
VC
2008
143views more  VC 2008»
14 years 9 months ago
A single-pass GPU ray casting framework for interactive out-of-core rendering of massive volumetric datasets
We present an adaptive out-of-core technique for rendering massive scalar volumes employing single pass GPU raycasting. The method is based on the decomposition of a volumetric dat...
Enrico Gobbetti, Fabio Marton, José Antonio...
IJCAI
2007
14 years 11 months ago
Compiling Bayesian Networks by Symbolic Probability Calculation Based on Zero-Suppressed BDDs
Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
Shin-ichi Minato, Ken Satoh, Taisuke Sato
78
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FUZZIEEE
2007
IEEE
15 years 4 months ago
Decoding Trace Peak Behaviour - A Neuro-Fuzzy Approach
— DNA sequence basecalling is commonly regarded as a solved problem, despite significant error rates being reflected in inaccuracies in databases and genome annotations. This has...
David Thornley, Stavros Petridis