Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
: Compression is the process of representing information in a compact form so as to reduce the bit rate for transmission or storage while maintaining acceptable fidelity or data qu...
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
In this paper, we present algorithms for Grid resource provisioning that employ agreement-based resource management. These algorithms allow userlevel resource allocation and sched...
Background: In population-based studies, it is generally recognized that single nucleotide polymorphism (SNP) markers are not independent. Rather, they are carried by haplotypes, ...