This paper presents an attempt at building a large scale distributed composite language model that simultaneously accounts for local word lexical information, mid-range sentence s...
The existence of good probabilistic models for the job arrival process and job characteristics is important for the improved understanding of grid systems and the prediction of th...
Michael Oikonomakos, Kostas Christodoulopoulos, Em...
Cache prediction for preemptive scheduling is an open issue despite its practical importance. First analysis approaches use simplified models for cache behavior or they assume si...
Abstract--In this paper we investigate the sparsity and recognition capabilities of two approximate Bayesian classification algorithms, the multi-class multi-kernel Relevance Vecto...
Ioannis Psorakis, Theodoros Damoulas, Mark A. Giro...
We present AutoDVS, a dynamic voltage scaling (DVS) system for hand-held computers. Unlike extant DVS systems, AutoDVS distinguishes common, course-grain, program behavior and cou...