Model selection is an important ingredient of many machine learning algorithms, in particular when the sample size in small, in order to strike the right trade-off between overfitt...
This paper analyzes the performance of semisupervised learning of mixture models. We show that unlabeled data can lead to an increase in classification error even in situations wh...
Fabio Gagliardi Cozman, Ira Cohen, Marcelo Cesar C...
This paper presents a methodology for accurately characterizing the system calls of an operating system for embedded applications. Characterization consists of two phases: measure...
—Interest in selection relaying is growing. The recent developments in this area have largely focused on information theoretic analyses such as outage performance. Some of these ...
This paper addresses the problem of determining the node locations in ad-hoc sensor networks when only connectivity information is available. In previous work, we showed that the ...