Journal Articles
2020(2 publications)
[publication]Lapa, P. and Castelli, M. and Ivo Gonçalves and Sala, E. and Rundo, L. , "A Hybrid End-to-End Approach Integrating Conditional Random Fields into CNNs for Prostate Cancer Detection on MRI", Applied Sciences,  vol. 10,  pp. 338-356, 2020

[publication]Manzoni, L. and Bartoli, A. and Castelli, M. and Ivo Gonçalves and Medvet, E. , "Specializing Context-Free Grammars with a (1 + 1)-EA", IEEE Transactions on Evolutionary Computation,  pp. 1-1, 2020

2019(1 publication)
[publication]Ivo Gonçalves and Gomes, Á. and Antunes, C.H. , "Optimizing the management of smart home energy resources under different power cost scenarios", Applied Energy,  vol. 242,  pp. 351-363, 2019

2018(3 publications)
[publication]Beretta, S. and Castelli, M. and Ivo Gonçalves and Kel, I. and Giansanti, V. and Merelli, I. , "Improving eQTL Analysis using a Machine Learning Approach for Data Integration: a Logistic Model Tree Solution", Journal of Computational Biology, 2018

[publication]Medvet, E. and Virgolin, M. and Castelli, M. and Bosman, P.A.N. and Ivo Gonçalves and Tušar, T. , "Unveiling Evolutionary Algorithm Representation with DU Maps", Genetic Programming and Evolvable Machines, 2018

[publication]Beretta, S. and Castelli, M. and Ivo Gonçalves and Henriques, R. and Ramazzotti, D. , "Learning the structure of Bayesian Networks: A quantitative assessment of the effect of different algorithmic schemes", Complexity, 2018

2017(2 publications)
[publication]Castelli, M. and Ivo Gonçalves and Trujillo, L. and Popovi?, A. , "An evolutionary system for ozone concentration forecasting", Information Systems Frontiers,  pp. 1123-1132, 2017

[publication]Castelli, M. and Trujillo, L. and Ivo Gonçalves and Popovi?, A. , "An evolutionary system for the prediction of high performance concrete strength based on semantic genetic programming", Computers and Concrete,  vol. 19,  pp. 651-658, 2017

Conference Articles
2019(4 publications)
[publication]Lapa, P. and Ivo Gonçalves and Rundo, L. and Castelli, M. , "Enhancing Classification Performance of Convolutional Neural Networks for Prostate Cancer Detection on Magnetic Resonance Images: a Study with the Semantic Learning Machine", in Genetic and Evolutionary Computation Conference, 2019

[publication]Lapa, P. and Ivo Gonçalves and Rundo, L. and Castelli, M. , "Semantic Learning Machine Improves the CNN-Based Detection of Prostate Cancer in Non-Contrast-Enhanced MRI", in Genetic and Evolutionary Computation Conference, 2019

[publication]Reis, I.F.G. and Ivo Gonçalves and Lopes, M.A.R. and Antunes, C.H. , "Residential demand-side flexibility in energy communities: a combination of optimization and agent modeling approaches", in International Conference on Smart Energy Systems and Technologies (SEST), 2019

[publication]Rasouli, V. and Ivo Gonçalves and Antunes, C.H. and Gomes, Á. , "A Comparison of MILP and Metaheuristic Approaches for Implementation of Home Energy Management System under Dynamic Tariffs", in International Conference on Smart Energy Systems and Technologies (SEST), 2019

2018(5 publications)
[publication]Castelli, M. and Ivo Gonçalves and Manzoni, L. and Vanneschi, L. , "Pruning Techniques for Mixed Ensembles of Genetic Programming Models", in 21st European Conference on Genetic Programming (EuroGP 2018), 2018

[publication]Ricardo, H. and Ivo Gonçalves and Costa, A.C. , "Forecasting tourism demand for Lisbon’s region through a data mining approach", in IADIS International Conference on Information Systems, 2018

[publication]Ivo Gonçalves and Gomes, Á. and Antunes, C.H. , "Optimizing Residential Energy Resources with an Improved Multi-Objective Genetic Algorithm based on Greedy Mutations", in Genetic and Evolutionary Computation Conference, 2018

[publication]Jagusch, J. and Ivo Gonçalves and Castelli, M. , "Neuroevolution under Unimodal Error Landscapes: An Exploration of the Semantic Learning Machine Algorithm", in Genetic and Evolutionary Computation Conference, 2018

[publication]Beretta, S. and Castelli, M. and Ivo Gonçalves and Ramazzotti, D. , "A quantitative assessment of the effect of different algorithmic schemes to the task of learning the structure of Bayesian Networks", in International conference on Computational Intelligence methods for Bioinformatics and Biostatistics, 2018

2017(4 publications)
[publication]Vanneschi, L. and Castelli, M. and Ivo Gonçalves and Manzoni, L. and Sara Silva , "Geometric Semantic Genetic Programming for Biomedical Applications: A State of the Art Upgrade", in IEEE Congress on Evolutionary Computation, 2017

[publication]Goribar-Jimenez, C. and Maldonado, Y. and Trujillo, L. and Castelli, M. and Ivo Gonçalves and Vanneschi, L. , "Towards the development of a complete GP system on an FPGA using geometric semantic operators", in IEEE Congress on Evolutionary Computation, 2017

[publication]Ivo Gonçalves and Sara Silva and Fonseca, C.M. and Castelli, M. , "Unsure When to Stop? Ask Your Semantic Neighbors", in Genetic and Evolutionary Computation Conference, 2017

[publication]Vanneschi, L. and Castelli, M. and Manzoni, L. and Krawiec, K. and Moraglio, A. and Sara Silva and Ivo Gonçalves , "PSXO - Population-Wide Semantic Crossover", in Genetic and Evolutionary Computation Conference, 2017

2016(4 publications)
[publication]Ivo Gonçalves and Sara Silva and Fonseca, C.M. and Castelli, M. , "Arbitrarily Close Alignments in the Error Space: A Geometric Semantic Genetic Programming Approach", in Genetic and Evolutionary Computation Conference, 2016

[publication]Beretta, S. and Castelli, M. and Ivo Gonçalves and Merelli, I. and Ramazzotti, D. , "Combining Bayesian Approaches and Evolutionary Techniques for the Inference of Breast Cancer Networks", in International Conference on Evolutionary Computation Theory and Applications, 2016

[publication]Castelli, M. and Manzoni, L. and Ivo Gonçalves and Vanneschi, L. and Trujillo, L. and Sara Silva , "An Analysis of Geometric Semantic Crossover: A Computational Geometry Approach", in International Conference on Evolutionary Computation Theory and Applications, 2016

[publication]Beretta, S. and Castelli, M. and Ivo Gonçalves and Kel, I. and Merelli, I. , "A Logistic Model Tree based Approach for eQTL Data Prediction Integration", in International conference on Computational Intelligence methods for Bioinformatics and Biostatistics, 2016

2015(2 publications)
[publication]Ivo Gonçalves and Sara Silva and Fonseca, C.M. , "On the Generalization Ability of Geometric Semantic Genetic Programming", in 18th European Conference on Genetic Programming (EuroGP 2015), 2015
[citation][year=2015]Dick, Grant, Aysha P. Rimoni, and Peter A. Whigham. "A Re-Examination of the Use of Genetic Programming on the Oral Bioavailability Problem." Proceedings of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.
[citation][year=2015]Graff, Mario, Eric Sadit Tellez, Elio Villasenor, and Sabino Miranda-Jiménez. "Semantic Genetic Programming Operators Based on Projections in the Phenotype Space."

[publication]Ivo Gonçalves and Sara Silva and Fonseca, C.M. , "Semantic Learning Machine: A Feedforward Neural Network Construction Algorithm Inspired by Geometric Semantic Genetic Programming", in 17th Portuguese Conference on Artificial Intelligence (EPIA 2015), 2015

2013(2 publications)
[publication]Ivo Gonçalves and Sara Silva , "Balancing Learning and Overfitting in Genetic Programming with Interleaved Sampling of Training Data", in 16th European Conference on Genetic Programming (EuroGP 2013), 2013
[citation][year=2015]Medernach, D., Fitzgerald, J., Azad, R., and Ryan, C.. "Wave: Incremental Erosion of Residual Error." Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.
[citation][year=2015]Žegklitz, Jan, and Petr Pošík. "Model Selection and Overfitting in Genetic Programming: Empirical Study." Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.
[citation][year=2015]Gonçalves, Eduardo C., Alexandre Plastino, and Alex A. Freitas. "Simpler is Better: a Novel Genetic Algorithm to Induce Compact Multi-label Chain Classifiers." Proceedings of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.
[citation][year=2015]Žegklitz, Jan, and Petr Pošík. "Model Selection and Overfitting in Genetic Programming: Empirical Study." arXiv preprint arXiv:1504.08168 (2015).
[citation][year=2014]Fitzgerald, Jeannie. "Bias and Variance Reduction Strategies for Improving Generalisation Performance of Genetic Programming on Binary Classification Tasks." PhD diss., University of Limerick, 2014.
[citation][year=2014]Azad, R., David Medernach, and Conor Ryan. "Efficient interleaved sampling of training data in genetic programming." In Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion, pp. 127-128. ACM, 2014.
[citation][year=2014]Muhammad Atif Azad, R., David Medernach, and Conor Ryan. "Efficient approaches to interleaved sampling of training data for symbolic regression." In Nature and Biologically Inspired Computing (NaBIC), 2014 Sixth World Congress on, pp. 176-183. IEEE, 2014.
[citation][year=2014]Goldstein, Evan B., and Giovanni Coco. "A machine learning approach for the prediction of settling velocity." Water Resources Research (2014).
[citation][year=2014]Martínez, Yuliana, Leonardo Trujillo, Enrique Naredo, and Pierrick Legrand. "A Comparison of Fitness-Case Sampling Methods for Symbolic Regression with Genetic Programming." EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (2014): 201-212.
[citation][year=2013]Gonçalves, Eduardo Corrêa, Alexandre Plastino, and Alex A. Freitas. "A Genetic Algorithm for Optimizing the Label Ordering in Multi-Label Classifier Chains." Proceedings of the 2013 25th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE Computer Society Conference Publishing Services (CPS), 2013.
[citation][year=2013]Goldstein, E. B., G. Coco, A. B. Murray, and M. O. Green. "Data driven components in a model of inner shelf sorted bedforms: a new hybrid model." Earth Surface Dynamics Discussions 1, no. 1 (2013): 531-569.

[publication]Sara Silva and Ingalalli, V. and Vinga, S. and Carreiras, J.M.B. and Melo, J. and Castelli, M. and Vanneschi, L. and Ivo Gonçalves and Caldas, J. , "Prediction of Forest Aboveground Biomass: An Exercise on Avoiding Overfitting", in EvoApplications, 2013
[citation][year=2014]Filippi, Anthony M., ?nci Güneralp, and Jarom Randall. "Hyperspectral remote sensing of aboveground biomass on a river meander bend using multivariate adaptive regression splines and stochastic gradient boosting." Remote Sensing Letters 5.5 (2014): 432-441.
[citation][year=2014]Güneralp, ?nci, Anthony M. Filippi, and Jarom Randall. "Estimation of floodplain aboveground biomass using multispectral remote sensing and nonparametric modeling." International Journal of Applied Earth Observation and Geoinformation 33 (2014): 119-126.

2012(1 publication)
[publication]Ivo Gonçalves and Sara Silva and Melo, J. and Carreiras, J.M.B. , "Random Sampling Technique for Overfitting Control in Genetic Programming", in 15th European Conference on Genetic Programming (EuroGP 2012), 2012
[citation][year=2015]Žegklitz, Jan, and Petr Pošík. "Model Selection and Overfitting in Genetic Programming: Empirical Study." Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.
[citation][year=2015]Garg, Akhil, and Kang Tai. "Evolving genetic programming models of higher generalization ability in modelling of turning process." Engineering Computations 32, no. 8 (2015)
[citation][year=2015]Kommenda, Michael, Michael Affenzeller, Gabriel Kronberger, Bogdan Burlacu, and Stephan Winkler. "Multi-Population Genetic Programming with Data Migration for Symbolic Regression." In Computational Intelligence and Efficiency in Engineering Systems, pp. 75-87. Springer International Publishing, 2015.
[citation][year=2015]Villar, José R., A. Enrique, Javier Sedano, and Marco A. García Tamargo. "Simple heuristics for enhancing GP learning." Logic Journal of IGPL (2015): jzv003.
[citation][year=2015]Žegklitz, Jan, and Petr Pošík. "Model Selection and Overfitting in Genetic Programming: Empirical Study." arXiv preprint arXiv:1504.08168 (2015).
[citation][year=2014]Garg, Akhil, Ankit Garg, K. Tai, and S. Sreedeep. "An integrated SRM-multi-gene genetic programming approach for prediction of factor of safety of 3-D soil nailed slopes." Engineering Applications of Artificial Intelligence (2014).
[citation][year=2014]Fitzgerald, Jeannie. "Bias and Variance Reduction Strategies for Improving Generalisation Performance of Genetic Programming on Binary Classification Tasks." PhD diss., University of Limerick, 2014.
[citation][year=2014]Garg, A., K. Tai, and M. M. Savalani. "Formulation of bead width model of an SLM prototype using modified multi-gene genetic programming approach." The International Journal of Advanced Manufacturing Technology (2014): 1-14.
[citation][year=2014]Haeri, Maryam Amir, Mohammad Mehdi Ebadzadeh, and Gianluigi Folino. "Improving GP generalization: a variance-based layered learning approach." Genetic Programming and Evolvable Machines: 1-29.
[citation][year=2014]Garg, Ankit, Akhil Garg, K. Tai, S. Barontini, and A. Stokes. "A Computational Intelligence-Based Genetic Programming Approach for the Simulation of Soil Water Retention Curves." Transport in Porous Media (2014): 1-17.
[citation][year=2014]Garg, Akhil, and Kang Tai. "An Improved Multi-Gene Genetic Programming Approach for the Evolution of Generalized Model in Modelling of Rapid Prototyping Process." In Modern Advances in Applied Intelligence, pp. 218-226. Springer International Publishing, 2014.
[citation][year=2014]Kommenda, Michael, Michael Affenzeller, Bogdan Burlacu, Gabriel Kronberger, and Stephan M. Winkler. "Genetic programming with data migration for symbolic regression." In Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion, pp. 1361-1366. ACM, 2014.
[citation][year=2013]Fitzgerald, Jeannie, R. Azad, and Conor Ryan. "A bootstrapping approach to reduce over-fitting in genetic programming." In Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion, pp. 1113-1120. ACM, 2013.
[citation][year=2013]Park, Namyong, Kangil Kim, and R. I. McKay. "Cutting evaluation costs: An investigation into early termination in genetic programming." In Evolutionary Computation (CEC), 2013 IEEE Congress on, pp. 3291-3298. IEEE, 2013.
[citation][year=2013]Kommenda, Michael, Gabriel Kronberger, Stephan Winkler, Michael Affenzeller, and Stefan Wagner. "Effects of constant optimization by nonlinear least squares minimization in symbolic regression." In Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion, pp. 1121-1128. ACM, 2013.
[citation][year=2013]Goldstein, E. B., G. Coco, A. B. Murray, and M. O. Green. "Data driven components in a model of inner shelf sorted bedforms: a new hybrid model." Earth Surface Dynamics Discussions 1, no. 1 (2013): 531-569.
[citation][year=2013]Goldstein, Evan B., Giovanni Coco, and A. Brad Murray. "Prediction of wave ripple characteristics using genetic programming." Continental Shelf Research (2013).

2011(2 publications)
[publication]Ribeiro, B. and Ivo Gonçalves and Santos, S. and Kovacec, A. , "Deep Learning Networks for Off-Line Handwritten Signature Recognition", in 16th Iberoamerican Congress on Pattern Recognition, C. San Martin and S.-W. Kim (Eds.): CIARP 2011, LNCS 7042, pp. 523-532, 2011. Springer-Verlag Berlin Heidelberg 2011, 2011
[citation][year=2015]Jabin, Suraiya, and Farhana Javed Zareen. "Biometric signature verification." International Journal of Biometrics 7.2 (2015): 97-118.
[citation][year=2015]Hafemann, Luiz G., Robert Sabourin, and Luiz S. Oliveira. "Offline Handwritten Signature Verification-Literature Review." arXiv preprint arXiv:1507.07909 (2015).
[citation][year=2015]Elwin, J. Granty Regina, and G. Kousalya. "Image Forgery Detection using Multidimensional Spectral Hashing based Polar Cosine Transform." Indian Journal of Science and Technology 8.S9 (2015): 128-139.
[citation][year=2015]Yilmaz, Mustafa Berkay. "Offline Signature Verification with User-Based and Global Classifiers of Local Features" PhD diss., Sabanc? University, 2015.
[citation][year=2014]Azmi, Aini Najwa, and Dewi Nasien. "Freeman Chain Code (FCC) Representation in Signature Fraud Detection Based On Nearest Neighbour and Artificial Neural Network (ANN) Classifiers." International Journal of Image Processing (IJIP) 8, no. 6 (2014): 434.

[publication]Ivo Gonçalves and Sara Silva , "Experiments on Controlling Overfitting in Genetic Programming", in Local proceedings of the 15th Portuguese Conference on Artificial Intelligence (EPIA 2011), 2011
[citation][year=2015]Žegklitz, Jan, and Petr Pošík. "Model Selection and Overfitting in Genetic Programming: Empirical Study." Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.
[citation][year=2015]Søren Atmakuri Davidsen, E. Sreedevi, and M. Padmavathamma. "Local and Global Genetic Fuzzy Pattern Classifiers." Machine Learning and Data Mining in Pattern Recognition
[citation][year=2015]Žegklitz, Jan, and Petr Pošík. "Model Selection and Overfitting in Genetic Programming: Empirical Study." arXiv preprint arXiv:1504.08168 (2015).
[citation][year=2014]Fitzgerald, Jeannie. "Bias and Variance Reduction Strategies for Improving Generalisation Performance of Genetic Programming on Binary Classification Tasks." PhD diss., University of Limerick, 2014.
[citation][year=2014]Urbano, Paulo, Enrique Naredo, and Leonardo Trujillo. "Generalization in Maze Navigation Using Grammatical Evolution and Novelty Search." In Theory and Practice of Natural Computing, pp. 35-46. Springer International Publishing, 2014.
[citation][year=2014]Martínez, Yuliana, Leonardo Trujillo, Enrique Naredo, and Pierrick Legrand. "A Comparison of Fitness-Case Sampling Methods for Symbolic Regression with Genetic Programming." EVOLVE-A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V (2014): 201-212.
[citation][year=2012]Martinez-Arellano, Giovanna, Lars Nolle, and John Bland. "Improving WRF-ARW Wind Speed Predictions using Genetic Programming." In Research and Development in Intelligent Systems XXIX, pp. 347-360. Springer London, 2012.

Book Chapters
2020(1 publication)
[publication]Ivo Gonçalves and Seca, M. and Castelli, M. , "Explorations of the Semantic Learning Machine Neuroevolution Algorithm: Dynamic Training Data Use, Ensemble Construction Methods, and Deep Learning Perspectives", in Genetic Programming Theory and Practice XVII,  vol. XVII,  pp. 1-24, 2020

PhD Theses
2017(1 publication)
[publication]Ivo Gonçalves , "An Exploration of Generalization and Overfitting in Genetic Programming: Standard and Geometric Semantic Approaches", 2017