Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
A key requirement for IETF recognition of new TCP algorithms is having an independent, interoperable implementation. This paper describes our BSD-licensed implementation of H-TCP ...
Grenville J. Armitage, Lawrence Stewart, Michael W...
— Understanding the behavior of emerging workloads is important for designing next generation microprocessors. For addressing this issue, computer architects and performance anal...
The logical and algorithmic properties of stable conditional independence (CI) as an alternative structural representation of conditional independence information are investigated...