While meta-heuristics are effective for solving large-scale combinatorial optimization problems, they result from time-consuming trial-and-error algorithm design tailored to speci...
Hoong Chuin Lau, Wee Chong Wan, Min Kwang Lim, Ste...
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
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 current embedded systems, one of the major concerns is energy conservation. The dynamic voltage-scheduling (DVS) framework, which involves dynamically adjusting the voltage and...
Ruibin Xu, Chenhai Xi, Rami G. Melhem, Daniel Moss...
Online aggregation is a promising solution to achieving fast early responses for interactive ad-hoc queries that compute aggregates on a large amount of data. Essential to the suc...