Efficiency enhancement techniques--such as parallelization and hybridization--are among the most important ingredients of practical applications of genetic and evolutionary algori...
We address the problem of optimizing the distribution of partially replicated databases over a computer network. Replication is used to increase data availability in the presence ...
Sarah Abdul-Wahid, Razvan Andonie, Joseph Lemley, ...
Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
We consider the problem of boosting the accuracy of weak learning algorithms in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992). Known algorithms for t...
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...