104 citations · 251 across the 6 of their papers we have counts for
6 papers
Infeasibility and structural bias in Differential Evolution
Fabio Caraffini, Anna V. Kononova, David Corne
This paper thoroughly investigates a range of popular DE configurations to identify components responsible for the emergence of structural bias - recently identified tendency of th…
Multi-objective evolutionary algorithms for quantum circuit discovery
Václav Potoček, Alan P. Reynolds, Alessandro Fedrizzi +1
Quantum hardware continues to advance, yet finding new quantum algorithms - quantum software - remains a challenge, with classically trained computer programmers having little intu…
Evolutionary Algorithms
David W. Corne, Michael A. Lones
Evolutionary algorithms (EAs) are population-based metaheuristics, originally inspired by aspects of natural evolution. Modern varieties incorporate a broad mixture of search mecha…
A 'Gibbs-Newton' Technique for Enhanced Inference of Multivariate Polya Parameters and Topic Models
Osama Khalifa, David Wolfe Corne, Mike Chantler
Hyper-parameters play a major role in the learning and inference process of latent Dirichlet allocation (LDA). In order to begin the LDA latent variables learning process, these hy…
Structural bias in population-based algorithms
Anna V. Kononova, David W. Corne, Philippe De Wilde +2
Challenging optimisation problems are abundant in all areas of science. Since the 1950s, scientists have developed ever-diversifying families of black box optimisation algorithms d…
Techniques for Highly Multiobjective Optimisation: Some Nondominated Points are Better than Others
David Corne, Joshua Knowles
The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much ev…