Abstract--In this paper, we present an efficient graph-based evolutionary optimization technique called evolutionary graph generation (EGG) and the proposed approach is applied to ...
Significant changes in the instance distribution or associated cost function of a learning problem require one to reoptimize a previously-learned classifier to work under new cond...
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E...
In this paper, we propose a new approach that consists of the extended compact genetic algorithm (ECGA) and split-ondemand (SoD), an adaptive discretization technique, to economic...
—Virtualized cloud-based services can take advantage of statistical multiplexing across applications to yield significant cost savings to the operator. However, achieving simila...
In this paper; we describe optimal algorithmsfor incorporating error recovery in the imprecise computation model. In that model eack task compriser a mandatory and an optional par...