| 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 | 40 | 2013 |
| 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 | 26 | 2014 |
| Design and analysis of schemes for adapting migration intervals in parallel evolutionary algorithms A Mambrini, D Sudholt Evolutionary Computation 23 (4), 559-582, 2015 | 25 | 2015 |
| 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 | 25 | 2013 |
| 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 | 20 | 2014 |
| 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 | 19 | 2012 |
| On the analysis of simple genetic programming for evolving Boolean functions A Mambrini, PS Oliveto Genetic Programming: 19th European Conference, EuroGP 2016, Porto, Portugal …, 2016 | 17 | 2016 |
| 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 | 10 | 2013 |
| 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 | 6 | 2014 |
| PRINCIPIA: a decentralized peer-review ecosystem A Mambrini, A Baronchelli, M Starnini, D Marinazzo, M De Domenico arXiv preprint arXiv:2008.09011, 2020 | 1 | 2020 |
| 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 | | |