Domain adaptation is a fundamental learning problem where one wishes to use labeled data from one or several source domains to learn a hypothesis performing well on a different, y...
This paper deals with the adaptive variance scaling issue in continuous Estimation of Distribution Algorithms. A phenomenon is discovered that current adaptive variance scaling me...
Abstract—This paper describes and evaluates a biologically-inspired network architecture that allows grid services to autonomously adapt to dynamic environment changes in the net...
In this paper we introduce an efficient implementation of asynchronously parallel genetic algorithm with adaptive genetic operators. The classic genetic algorithm paradigm is exte...
A matrix formulation for an adaptive genetic algorithm is developed using mutation matrix and crossover matrix. Selection, mutation, and crossover are all parameter-free in the se...