Sara Silva

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Leonardo VanneschiNOVA IMS, Universidade Nova de LisboaVerified email at isegi.unl.pt
Mauro CastelliNOVA IMS, Universidade Nova de LisboaVerified email at novaims.unl.pt
Leonardo TrujilloInstituto Tecnológico de TIjuanaVerified email at tectijuana.edu.mx
Luca ManzoniDipartimento di Matematica e Geoscienze, Università degli Studi di TriesteVerified email at units.it
Ivo GonçalvesUniversity of CoimbraVerified email at dei.uc.pt
maria vasconcelosSchool of Agriculture, The University of LisbonVerified email at isa.ulisboa.pt
Luis Muñoz DelgadoDoctor en ciencias de la ingenieríaVerified email at tectijuana.edu.mx
Ernesto CostaProfessor of Computer Science, University of CoimbraVerified email at dei.uc.pt
Alberto MoraglioUniversity of ExeterVerified email at exeter.ac.uk
Carlos M. FonsecaDepartment of Informatics Engineering, University of CoimbraVerified email at dei.uc.pt
João CarreirasNational Centre for Earth Observation (NCEO), University of Sheffield, United KingdomVerified email at sheffield.ac.uk
Margarida TomeProfessor of Forest BiometricsVerified email at isa.ulisboa.pt
William La CavaUniversity of PennsylvaniaVerified email at upenn.edu
Lee SpectorProfessor of Computer Science, Hampshire CollegeVerified email at hampshire.edu
Jason H. MooreProfessor and Director, Institute for Biomedical Informatics, University of PennsylvaniaVerified email at upenn.edu
Enrique NaredoUniversity of Limerick, Ireland.Verified email at ul.ie
Stefano RubertoPenn, University of PennsylvaniaVerified email at gssi.infn.it
Julian TogeliusAssociate Professor of Computer Science and Engineering, New York University; co-founder, modl.aiVerified email at nyu.edu
Catia PesquitaLASIGE, Dep. Informática, Faculdade de Ciências, Universidade de Lisboa, PortugalVerified email at xldb.di.fc.ul.pt
José S. Uva (Paúl)Centro de Estudos Florestais | ForChange: Forest ecosystem management under global changeVerified email at icnf.pt

Sara Silva

Principal Investigator, LASIGE, Departamento de Informática, Faculdade de Ciências, Universidade de

Verified email at fc.ul.pt - Homepage

Genetic Programming Machine Learning


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GPLAB-a genetic programming toolbox for MATLAB S Silva, J Almeida Proceedings of the Nordic MATLAB conference, 273-278, 2003	319	2003
GPLAB-a genetic programming toolbox for MATLAB S Silva, J Almeida Proceedings of the Nordic MATLAB conference, 273-278, 2003	291	2003
Spatial prediction of fire ignition probabilities: comparing logistic regression and neural networks MJP de Vasconcelos, S Silva, M Tome, M Alvim, JMC Pereira Photogrammetric Engineering and Remote Sensing 67 (1), 73-81, 2001	267	2001
Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics): Preface M Abe, K Aoki, G Ateniese, R Avanzi, Z Beerliová, O Billet, A Biryukov, ... Lecture Notes in Computer Science (including subseries Lecture Notes in …, 2006	176*	2006
A survey of semantic methods in genetic programming L Vanneschi, M Castelli, S Silva Genetic Programming and Evolvable Machines 15 (2), 195-214, 2014	152	2014
Dynamic limits for bloat control in genetic programming and a review of past and current bloat theories S Silva, E Costa Genetic Programming and Evolvable Machines 10 (2), 141-179, 2009	150	2009
Measuring bloat, overfitting and functional complexity in genetic programming L Vanneschi, M Castelli, S Silva Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010	116	2010
Dynamic maximum tree depth - a simple technique for avoiding bloat in tree-based GP S Silva, J Almeida Genetic and Evolutionary Computation—GECCO 2003, 1776-1787, 2003	115*	2003
A C++ framework for geometric semantic genetic programming M Castelli, S Silva, L Vanneschi Genetic Programming and Evolvable Machines 16 (1), 73-81, 2015	104	2015
A new implementation of geometric semantic GP and its application to problems in pharmacokinetics L Vanneschi, M Castelli, L Manzoni, S Silva European Conference on Genetic Programming, 205-216, 2013	103	2013
Prediction of high performance concrete strength using genetic programming with geometric semantic genetic operators M Castelli, L Vanneschi, S Silva Expert Systems with Applications 40 (17), 6856-6862, 2013	87	2013
Urban biodiversity: a review of current concepts and contributions to multidisciplinary approaches P Farinha-Marques, JM Lameiras, C Fernandes, S Silva, F Guilherme Innovation: The European Journal of Social Science Research 24 (3), 247-271, 2011	83	2011
Geometric semantic genetic programming for real life applications L Vanneschi, S Silva, M Castelli, L Manzoni Genetic programming theory and practice xi, 191-209, 2014	80	2014
Dynamic limits for bloat control - variations on size and depth S Silva, E Costa Genetic and Evolutionary Computation–GECCO 2004, 666-677, 2004	68*	2004
Balancing learning and overfitting in genetic programming with interleaved sampling of training data I Gonçalves, S Silva European Conference on Genetic Programming, 73-84, 2013	65	2013
Random sampling technique for overfitting control in genetic programming I Gonçalves, S Silva, JB Melo, JMB Carreiras European Conference on Genetic Programming, 218-229, 2012	56	2012
Operator equalisation for bloat free genetic programming and a survey of bloat control methods S Silva, S Dignum, L Vanneschi Genetic Programming and Evolvable Machines 13 (2), 197-238, 2012	55	2012
Prediction of the unified Parkinson’s disease rating scale assessment using a genetic programming system with geometric semantic genetic operators M Castelli, L Vanneschi, S Silva Expert Systems with Applications 41 (10), 4608-4616, 2014	50	2014
neat Genetic Programming: Controlling bloat naturally L Trujillo, L Muñoz, E Galván-López, S Silva Information Sciences 333, 21-43, 2016	42	2016
Operator equalisation, bloat and overfitting: a study on human oral bioavailability prediction S Silva, L Vanneschi Proceedings of the 11th Annual conference on Genetic and evolutionary …, 2009	39	2009

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