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DILS
2009
Springer
15 years 6 months ago
Integration of Full-Coverage Probabilistic Functional Networks with Relevance to Specific Biological Processes
Probabilistic functional integrated networks are powerful tools with which to draw inferences from high-throughput data. However, network analyses are generally not tailored to spe...
Katherine James, Anil Wipat, Jennifer Hallinan
NIPS
1992
15 years 28 days ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
FLAIRS
2004
15 years 1 months ago
An Application of Neural Networks to Sequence Analysis and Genre Identification
This study borrowed sequence analysis techniques from the genetic sciences and applied them to a similar problem in email filtering and web searching. Genre identification is the ...
David Bisant
ICML
2005
IEEE
16 years 18 days ago
Learning class-discriminative dynamic Bayesian networks
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
John Burge, Terran Lane
ICASSP
2011
IEEE
14 years 3 months ago
Online anomaly detection with expert system feedback in social networks
In this paper, we propose examining the participants in various meetings or communications within a social network, and using sequential inference based on these participant lists...
Corinne Horn, Rebecca Willett