Abstract We explore the problem of portable and flexible privacy preserving access rights that permit access to a large collection of digital goods. Privacy-preserving access contr...
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
A learning problem that has only recently gained attention in the machine learning community is that of learning a classifier from group probabilities. It is a learning task that ...