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AI
2002
Springer
13 years 7 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
NN
2007
Springer
13 years 6 months ago
Optimal decision network with distributed representation
On the basis of detailed analysis of reaction times and neurophysiological data from tasks involving choice, it has been proposed that the brain implements an optimal statistical ...
Rafal Bogacz
IPPS
1999
IEEE
13 years 11 months ago
A Communication Latency Hiding Parallelization of a Traffic Flow Simulation
This work implements and analyses a highway traffic flow simulation based on continuum modeling of traffic dynamics. A traffic-flow simulation was developed and mapped onto a para...
Charles Michael Johnston, Anthony T. Chronopoulos
BMCBI
2006
239views more  BMCBI 2006»
13 years 7 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
HPDC
2002
IEEE
14 years 10 days ago
Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications
In high energy physics, bioinformatics, and other disciplines, we encounter applications involving numerous, loosely coupled jobs that both access and generate large data sets. So...
Kavitha Ranganathan, Ian T. Foster