Abstract. The problem of classification from positive and unlabeled examples attracts much attention currently. However, when the number of unlabeled negative examples is very sma...
Xiaoling Wang, Zhen Xu, Chaofeng Sha, Martin Ester...
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
The problem of optimization of subband coders for given input statistics has received considerable attention in recent literature. The goal in these works has been to maximize the...
As the properties of components have gradually become clearer, attention has started to turn to the architectural issues which govern their interaction and composition. In this pa...
There is tremendous demand for the ability to be able to electronically buy and sell goods over networks. This field is called electronic commerce, and it has inspired a large var...