We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
This paper presents an active learning method that directly optimizes expected future error. This is in contrast to many other popular techniques that instead aim to reduce versio...
When implementing persistent objects on a relational database, a major performance issue is prefetching data to minimize the number of roundtrips to the database. This is especial...
Current trends signal an imminent crisis in the simulation of future CMPs (Chip MultiProcessors). Future micro-architectures will offer more and more thread contexts to execute pa...
Jianwei Chen, Lakshmi Kumar Dabbiru, Daniel Wong, ...
Background: The increasing availability of molecular sequence data means that the accuracy of future phylogenetic studies is likely to by limited by systematic bias and taxon choi...
Martin O. Jones, Georgios D. Koutsovoulos, Mark L....