Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
In this paper, an object-oriented unified optimization framework (UOF) for general problem optimization is proposed. Based on evolutionary algorithms, numerical deterministic meth...
Some compilation systems, such as offline partial evaluators and selective dynamic compilation systems, support staged optimizations. A staged optimization is one where a logicall...
Matthai Philipose, Craig Chambers, Susan J. Eggers
—This paper introduces a novel deployment time optimization technology for Internet services. Using the configuration information collected from the operation environment, the pr...
Sang Jeong Lee, Kang-Won Lee, Kyung Dong Ryu, Jong...