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...
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...
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 ...
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...
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...