Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Grid Workflows are emerging as practical programming models for solving large e-scientific problems on the Grid. However, it is typically assumed that the workflow components eith...
Background: Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-seq) or ChIP followed by genome tiling array analysis (ChIP-chip) have become standar...
Lihua J. Zhu, Claude Gazin, Nathan D. Lawson, Herv...
Abstract— Cycle-harvesting software on commodity computers is available from a number of companies and a significant part of the Grid computing landscape. However, creating comm...
The number of functional errors escaping design verification and being released into final silicon is growing, due to the increasing complexity and shrinking production schedules ...