15 citations · 20 across the 3 of their papers we have counts for
3 papers
Machine learning with incomplete datasets using multi-objective optimization models
Hadi A. Khorshidi, Michael Kirley, Uwe Aickelin
Machine learning techniques have been developed to learn from complete data. When missing values exist in a dataset, the incomplete data should be preprocessed separately by removi…
Dynamic Multi-objective Optimization of the Travelling Thief Problem
Daniel Herring, Michael Kirley, Xin Yao
Investigation of detailed and complex optimisation problem formulations that reflect realistic scenarios is a burgeoning field of research. A growing body of work exists for the Tr…
Multi-Objective Problem Solving With Offspring on Enterprise Clouds
Christian Vecchiola, Michael Kirley, Rajkumar Buyya
In this paper, we present a distributed implementation of a network based multi-objective evolutionary algorithm, called EMO, by using Offspring. Network based evolutionary algorit…