Andrea Mambrini
Andrea Mambrini
Optidrome
Verified email at optidrome.com - Homepage
Title
Cited by
Cited by
Year
Runtime analysis of mutation-based geometric semantic genetic programming for basis functions regression
A Moraglio, A Mambrini
Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013
312013
Runtime analysis of mutation-based geometric semantic genetic programming on boolean functions
A Moraglio, A Mambrini, L Manzoni
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII …, 2013
212013
Design and analysis of adaptive migration intervals in parallel evolutionary algorithms
A Mambrini, D Sudholt
Proceedings of the 2014 annual conference on genetic and evolutionary …, 2014
172014
Homogeneous and Heterogeneous Island Models for the Set Cover Problem
A Mambrini, D Sudholt, X Yao
Parallel Problem Solving from Nature-PPSN XII, 11-20, 2012
162012
PaDe: A parallel algorithm based on the MOEA/D framework and the island model
A Mambrini, D Izzo
International Conference on Parallel Problem Solving from Nature, 711-720, 2014
142014
Design and analysis of schemes for adapting migration intervals in parallel evolutionary algorithms
A Mambrini, D Sudholt
Evolutionary Computation 23 (4), 559-582, 2015
122015
On the analysis of simple genetic programming for evolving boolean functions
A Mambrini, PS Oliveto
European Conference on Genetic Programming, 99-114, 2016
82016
Theory-laden design of mutation-based geometric semantic genetic programming for learning classification trees
A Mambrini, L Manzoni, A Moraglio
2013 IEEE Congress on Evolutionary Computation, 416-423, 2013
82013
A comparison between geometric semantic GP and cartesian GP for Boolean functions learning
A Mambrini, L Manzoni
Proceedings of the Companion Publication of the 2014 Annual Conference on …, 2014
52014
Theory grounded design of genetic programming and parallel evolutionary algorithms
A Mambrini
University of Birmingham, 2015
2015
A framework for measuring the generalization ability of Geometric Semantic Genetic Programming (GSGP) for Black-Box Boolean Functions Learning
A Mambrini, Y Yu, X Yao
The system can't perform the operation now. Try again later.
Articles 1–11