We examine the ability to exploit the hierarchical structure of Internet addresses in order to endow network agents with predictive capabilities. Specifically, we consider Suppor...
Analysis of biological data often involves large data sets and computationally expensive algorithms. Databases of biological data continue to grow, leading to an increasing demand ...
The Bayesian committee machine (BCM) is a novel approach to combining estimators which were trained on different data sets. Although the BCM can be applied to the combination of a...
The two main challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models ...
3D neuro-anatomical images and other volumetric data sets are important in many scientific and biomedical fields. Since such sets may be extremely large, a scalable compression me...