Abstract. We present a Bayesian translational model for matching patterns in data sets which have neither co-occurring samples nor variables, but only a similar experiment design d...
Tommi Suvitaival, Ilkka Huopaniemi, Matej Oresic, ...
We carry forward the work described in our previous papers [3, 14, 12] on the application of data independence to the model checking of cryptographic protocols using CSP [13] and ...
Abstract— Automatic pattern classifiers that allow for incremental learning can adapt internal class models efficiently in response to new information, without having to retrai...
In the study of information flow in the nervous system, component processes can be investigated using a range of electrophysiological and imaging techniques. Although data is diff...
Despite a large body of literature and methods devoted to the Traffic Matrix (TM) estimation problem, the inference of traffic flows volume from aggregated data still represents a ...