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ORCIDLeonardo Vanneschi
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- affiliation: Universidade Nova de Lisboa, Portugal
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2020 – today
- 2024
[j92]Nuno M. Rodrigues
, José Guilherme de Almeida, Ana Sofia Castro Verde, Ana Mascarenhas Gaivão, Carlos Bilreiro, Inês Santiago, Joana Ip, Sara Belião, Raquel Moreno, Celso Matos, Leonardo Vanneschi, Manolis Tsiknakis, Kostas Marias, Daniele Regge, Sara Silva, Nickolas Papanikolaou:
Analysis of domain shift in whole prostate gland, zonal and lesions segmentation and detection, using multicentric retrospective data. Comput. Biol. Medicine 171: 108216 (2024)- [j91]Nuno Miguel Rodrigues, José Guilherme de Almeida, Ana Sofia Castro Verde, Ana Mascarenhas Gaivão, Carlos Bilreiro, Inês Santiago, Joana Ip, Sara Belião, Raquel Moreno, Celso Matos, Leonardo Vanneschi, Manolis Tsiknakis, Kostas Marias, Daniele Regge, Sara Silva, Nickolas Papanikolaou:
Corrigendum to "Analysis of domain shift in whole prostate gland, zonal and lesions segmentation and detection, using multicentric retrospective data" [Comput. Biol. Med. 17 (2024) 108216]. Comput. Biol. Medicine 173: 108352 (2024) - [j90]Illya Bakurov, Jose Manuel Muñoz Contreras, Mauro Castelli, Nuno M. Rodrigues, Sara Silva, Leonardo Trujillo, Leonardo Vanneschi:
Geometric semantic genetic programming with normalized and standardized random programs. Genet. Program. Evolvable Mach. 25(1): 6 (2024) - [j89]Giorgia Nadizar, Berfin Sakallioglu, Fraser Garrow, Sara Silva, Leonardo Vanneschi:
Geometric semantic GP with linear scaling: Darwinian versus Lamarckian evolution. Genet. Program. Evolvable Mach. 25(2): 17 (2024) - [j88]Davide Farinati, Leonardo Vanneschi:
A survey on dynamic populations in bio-inspired algorithms. Genet. Program. Evolvable Mach. 25(2): 19 (2024) - [j87]Nuno M. Rodrigues, João E. Batista, William G. La Cava, Leonardo Vanneschi, Sara Silva:
Exploring SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming. SN Comput. Sci. 5(1): 91 (2024) - [j86]Irene Azzali, Nicole Dalia Cilia, Claudio De Stefano, Francesco Fontanella, Mario Giacobini, Leonardo Vanneschi:
Automatic feature extraction with Vectorial Genetic Programming for Alzheimer's Disease prediction through handwriting analysis. Swarm Evol. Comput. 87: 101571 (2024) - [c136]João Eduardo Batista, Nuno Miguel Rodrigues, Leonardo Vanneschi, Sara Silva:
M6GP: Multiobjective Feature Engineering. CEC 2024: 1-8 - [c135]Francesco Marchetti, Mauro Castelli, Illya Bakurov, Leonardo Vanneschi:
Full Inclusive Genetic Programming. CEC 2024: 1-8 - [c134]Leonardo Vanneschi:
SLIM_GSGP: The Non-bloating Geometric Semantic Genetic Programming. EuroGP 2024: 125-141 - [c133]Davide Farinati, Leonardo Vanneschi:
GM4OS: An Evolutionary Oversampling Approach for Imbalanced Binary Classification Tasks. EvoApplications@EvoStar 2024: 68-82 - 2023
- [b1]Leonardo Vanneschi, Sara Silva:
Lectures on Intelligent Systems. Natural Computing Series, Springer 2023, ISBN 978-3-031-17921-1, pp. 1-331 - [j85]Karina Brotto Rebuli, Laura Ozella, Leonardo Vanneschi, Mario Giacobini:
Multi-algorithm clustering analysis for characterizing cow productivity on automatic milking systems over lactation periods. Comput. Electron. Agric. 211: 108002 (2023) - [j84]Daniele M. Papetti, Andrea Tangherloni, Davide Farinati, Paolo Cazzaniga, Leonardo Vanneschi:
Simplifying Fitness Landscapes Using Dilation Functions Evolved With Genetic Programming. IEEE Comput. Intell. Mag. 18(1): 22-31 (2023) - [j83]Illya Bakurov, Marco Buzzelli, Raimondo Schettini, Mauro Castelli, Leonardo Vanneschi:
Semantic segmentation network stacking with genetic programming. Genet. Program. Evolvable Mach. 24(2): 15 (2023) - [j82]Leonardo Vanneschi, Leonardo Trujillo:
Introduction to the peer commentary special section on "Jaws 30" by W. B. Langdon. Genet. Program. Evolvable Mach. 24(2): 18 (2023) - [j81]Davide Farinati, Illya Bakurov, Leonardo Vanneschi:
A study of dynamic populations in geometric semantic genetic programming. Inf. Sci. 648: 119513 (2023) - [j80]Illya Bakurov, Marco Buzzelli, Raimondo Schettini, Mauro Castelli, Leonardo Vanneschi:
Full-Reference Image Quality Expression via Genetic Programming. IEEE Trans. Image Process. 32: 1458-1473 (2023) - [c132]Pedro Carvalho, Bruno Ribeiro, Nuno M. Rodrigues, João E. Batista, Leonardo Vanneschi, Sara Silva:
Feature Selection on Epistatic Problems Using Genetic Algorithms with Nested Classifiers. EvoApplications@EvoStar 2023: 656-671 - [c131]Philipp Fleck, Stephan M. Winkler, Michael Kommenda, Sara Silva, Leonardo Vanneschi, Michael Affenzeller:
Evolutionary Algorithms for Segment Optimization in Vectorial GP. GECCO Companion 2023: 439-442 - [c130]Karina Brotto Rebuli, Mario Giacobini, Sara Silva, Leonardo Vanneschi:
A Comparison of Structural Complexity Metrics for Explainable Genetic Programming. GECCO Companion 2023: 539-542 - [c129]Giorgia Nadizar, Fraser Garrow, Berfin Sakallioglu, Lorenzo Canonne, Sara Silva, Leonardo Vanneschi:
An Investigation of Geometric Semantic GP with Linear Scaling. GECCO 2023: 1165-1174 - [e6]Claudio De Stefano, Francesco Fontanella, Leonardo Vanneschi:
Artificial Life and Evolutionary Computation - 16th Italian Workshop, WIVACE 2022, Gaeta, Italy, September 14-16, 2022, Revised Selected Papers. Communications in Computer and Information Science 1780, Springer 2023, ISBN 978-3-031-31182-6 [contents] - 2022
- [j79]Illya Bakurov, Marco Buzzelli, Raimondo Schettini, Mauro Castelli, Leonardo Vanneschi:
Structural similarity index (SSIM) revisited: A data-driven approach. Expert Syst. Appl. 189: 116087 (2022) - [j78]Paula Cruz, Leonardo Vanneschi, Marco Painho, Paulo Rita:
Automatic Identification of Addresses: A Systematic Literature Review. ISPRS Int. J. Geo Inf. 11(1): 11 (2022) - [j77]Nuno M. Rodrigues, Katherine M. Malan, Gabriela Ochoa, Leonardo Vanneschi, Sara Silva:
Fitness landscape analysis of convolutional neural network architectures for image classification. Inf. Sci. 609: 711-726 (2022) - [j76]Eftychia Koukouraki, Leonardo Vanneschi, Marco Painho:
Few-Shot Learning for Post-Earthquake Urban Damage Detection. Remote. Sens. 14(1): 40 (2022) - [j75]Karina Brotto Rebuli, Leonardo Vanneschi:
An Empirical Study of Progressive Insular Cooperative GP. SN Comput. Sci. 3(2): 119 (2022) - [j74]Illya Bakurov, Mauro Castelli, Francesco Fontanella, Alessandra Scotto di Freca, Leonardo Vanneschi:
A novel binary classification approach based on geometric semantic genetic programming. Swarm Evol. Comput. 69: 101028 (2022) - [c128]Giacomo Zoppi, Leonardo Vanneschi, Mario Giacobini:
Reducing the Number of Training Cases in Genetic Programming. CEC 2022: 1-8 - [c127]Nuno M. Rodrigues, João E. Batista, William G. La Cava, Leonardo Vanneschi, Sara Silva:
SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming. EuroGP 2022: 68-84 - [c126]Irene Azzali, Nicole Dalia Cilia, Claudio De Stefano, Francesco Fontanella, Mario Giacobini, Leonardo Vanneschi:
Vectorial GP for Alzheimer's Disease Prediction Through Handwriting Analysis. EvoApplications 2022: 517-530 - [c125]Karina Brotto Rebuli, Mario Giacobini, Niccolò Tallone, Leonardo Vanneschi:
A preliminary study of prediction interval methods with genetic programming. GECCO Companion 2022: 530-533 - [c124]Illya Bakurov, Marco Buzzelli, Mauro Castelli, Raimondo Schettini, Leonardo Vanneschi:
Genetic programming for structural similarity design at multiple spatial scales. GECCO 2022: 911-919 - [c123]Karina Brotto Rebuli, Mario Giacobini, Niccolò Tallone, Leonardo Vanneschi:
Single and Multi-objective Genetic Programming Methods for Prediction Intervals. WIVACE 2022: 205-218 - [c122]Liah Rosenfeld, Leonardo Vanneschi:
EGSGP: An Ensemble System Based on Geometric Semantic Genetic Programming. WIVACE 2022: 278-290 - 2021
- [j73]Leonardo Vanneschi, Mauro Castelli:
Soft target and functional complexity reduction: A hybrid regularization method for genetic programming. Expert Syst. Appl. 177: 114929 (2021) - [j72]João E. Batista, Ana I. R. Cabral, Maria J. P. de Vasconcelos, Leonardo Vanneschi, Sara Silva:
Improving Land Cover Classification Using Genetic Programming for Feature Construction. Remote. Sens. 13(9): 1623 (2021) - [j71]Illya Bakurov, Mauro Castelli, Olivier Gau, Francesco Fontanella, Leonardo Vanneschi:
Genetic programming for stacked generalization. Swarm Evol. Comput. 65: 100913 (2021) - [c121]Karina Brotto Rebuli, Leonardo Vanneschi:
Progressive Insular Cooperative GP. EuroGP 2021: 19-35 - [i8]Nuno M. Rodrigues, João E. Batista, Leonardo Trujillo, Bernardo Duarte, Mario Giacobini, Leonardo Vanneschi, Sara Silva:
Plotting time: On the usage of CNNs for time series classification. CoRR abs/2102.04179 (2021) - 2020
- [j70]Nuno M. Rodrigues, Sara Silva, Leonardo Vanneschi:
A Study of Generalization and Fitness Landscapes for Neuroevolution. IEEE Access 8: 108216-108234 (2020) - [j69]Irene Azzali, Leonardo Vanneschi, Illya Bakurov, Sara Silva, Marco Ivaldi, Mario Giacobini:
Towards the use of vector based GP to predict physiological time series. Appl. Soft Comput. 89: 106097 (2020) - [j68]Alfredo Raglio, Marcello Imbriani, Chiara Imbriani, Paola Baiardi, Sara Manzoni, Marta Gianotti, Mauro Castelli, Leonardo Vanneschi, Francisco Vico, Luca Manzoni:
Machine learning techniques to predict the effectiveness of music therapy: A randomized controlled trial. Comput. Methods Programs Biomed. 185: 105160 (2020) - [j67]Mauro Castelli, Maria Dobreva, Roberto Henriques, Leonardo Vanneschi:
Predicting Days on Market to Optimize Real Estate Sales Strategy. Complex. 2020: 4603190:1-4603190:22 (2020) - [j66]Mauro Castelli, Fabiana Martins Clemente, Ales Popovic, Sara Silva, Leonardo Vanneschi:
A Machine Learning Approach to Predict Air Quality in California. Complex. 2020: 8049504:1-8049504:23 (2020) - [j65]Daniela Besozzi, Luca Manzoni, Marco S. Nobile, Simone Spolaor, Mauro Castelli, Leonardo Vanneschi, Paolo Cazzaniga, Stefano Ruberto, Leonardo Rundo, Andrea Tangherloni:
Computational Intelligence for Life Sciences. Fundam. Informaticae 171(1-4): 57-80 (2020) - [j64]Irene Azzali, Leonardo Vanneschi, Andrea Mosca, Luigi Bertolotti, Mario Giacobini:
Towards the use of genetic programming in the ecological modelling of mosquito population dynamics. Genet. Program. Evolvable Mach. 21(4): 629-642 (2020) - [c120]Francesca Abbona, Leonardo Vanneschi, Marco Bona, Mario Giacobini:
A GP approach for precision farming. CEC 2020: 1-8 - [c119]Nuno M. Rodrigues, Sara Silva, Leonardo Vanneschi:
A Study of Fitness Landscapes for Neuroevolution. CEC 2020: 1-8 - [c118]Irene Azzali, Leonardo Vanneschi, Mario Giacobini:
Investigating the Use of Geometric Semantic Operators in Vectorial Genetic Programming. EuroGP 2020: 52-67 - [c117]Leonardo Vanneschi, Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Trujillo:
Is k Nearest Neighbours Regression Better Than GP? EuroGP 2020: 244-261 - [c116]Leonardo Lucio Custode, Ciro Lucio Tecce, Illya Bakurov, Mauro Castelli, Antonio Della Cioppa, Leonardo Vanneschi:
A Greedy Iterative Layered Framework for Training Feed Forward Neural Networks. EvoApplications 2020: 513-529 - [c115]Uriel López, Leonardo Trujillo, Sara Silva, Leonardo Vanneschi, Pierrick Legrand:
Unlabeled multi-target regression with genetic programming. GECCO 2020: 976-984 - [i7]Nuno M. Rodrigues, Sara Silva, Leonardo Vanneschi:
A Study of Fitness Landscapes for Neuroevolution. CoRR abs/2001.11272 (2020)
2010 – 2019
- 2019
- [j63]Petr Hájek, Roberto Henriques, Mauro Castelli, Leonardo Vanneschi:
Forecasting performance of regional innovation systems using semantic-based genetic programming with local search optimizer. Comput. Oper. Res. 106: 179-190 (2019) - [j62]Luis Muñoz, Leonardo Trujillo, Sara Silva, Mauro Castelli, Leonardo Vanneschi:
Evolving multidimensional transformations for symbolic regression with M3GP. Memetic Comput. 11(2): 111-126 (2019) - [j61]William G. La Cava, Sara Silva, Kourosh Danai, Lee Spector, Leonardo Vanneschi, Jason H. Moore:
Multidimensional genetic programming for multiclass classification. Swarm Evol. Comput. 44: 260-272 (2019) - [j60]Stefano Ruberto, Leonardo Vanneschi, Mauro Castelli:
Genetic programming with semantic equivalence classes. Swarm Evol. Comput. 44: 453-469 (2019) - [j59]Mauro Castelli, Gianpiero Cattaneo, Luca Manzoni, Leonardo Vanneschi:
A distance between populations for n-points crossover in genetic algorithms. Swarm Evol. Comput. 44: 636-645 (2019) - [j58]Leonardo Vanneschi, Mauro Castelli, Kristen M. Scott, Leonardo Trujillo:
Alignment-based genetic programming for real life applications. Swarm Evol. Comput. 44: 840-851 (2019) - [j57]Álvaro Rubio-Largo, Leonardo Vanneschi, Mauro Castelli, Miguel A. Vega-Rodríguez:
Multiobjective Metaheuristic to Design RNA Sequences. IEEE Trans. Evol. Comput. 23(1): 156-169 (2019) - [c114]Eunice Carrasquinha, João Santinha, Alexander Mongolin, Maria Lisitskiya, Joana Ribeiro, Fátima Cardoso, Celso Matos, Leonardo Vanneschi, Nikolaos Papanikolaou:
Regularization Techniques in Radiomics: A Case Study on the Prediction of pCR in Breast Tumours and the Axilla. CIBB 2019: 271-281 - [c113]Irene Azzali, Leonardo Vanneschi, Sara Silva, Illya Bakurov, Mario Giacobini:
A Vectorial Approach to Genetic Programming. EuroGP 2019: 213-227 - [c112]Illya Bakurov, Mauro Castelli, Leonardo Vanneschi, Maria João Freitas:
Supporting Medical Decisions for Treating Rare Diseases Through Genetic Programming. EvoApplications 2019: 187-203 - [c111]Illya Bakurov, Mauro Castelli, Francesco Fontanella, Leonardo Vanneschi:
A Regression-like Classification System for Geometric Semantic Genetic Programming. IJCCI 2019: 40-48 - [c110]Alessandro Re, Leonardo Vanneschi, Mauro Castelli:
Universal Learning Machine with Genetic Programming. IJCCI 2019: 115-122 - [r3]Mauro Castelli, Leonardo Vanneschi, Álvaro Rubio-Largo:
Supervised Learning: Classification. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 342-349 - [r2]Leonardo Vanneschi, Mauro Castelli:
Multilayer Perceptrons. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 612-620 - [r1]Leonardo Vanneschi, Mauro Castelli:
Delta Rule and Backpropagation. Encyclopedia of Bioinformatics and Computational Biology (1) 2019: 621-633 - 2018
- [j56]Álvaro Rubio-Largo, Leonardo Vanneschi, Mauro Castelli, Miguel A. Vega-Rodríguez:
Multiobjective characteristic-based framework for very-large multiple sequence alignment. Appl. Soft Comput. 69: 719-736 (2018) - [j55]Leonardo Vanneschi, David Micha Horn, Mauro Castelli, Ales Popovic:
An artificial intelligence system for predicting customer default in e-commerce. Expert Syst. Appl. 104: 1-21 (2018) - [j54]Álvaro Rubio-Largo, Mauro Castelli, Leonardo Vanneschi, Miguel A. Vega-Rodríguez:
A Parallel Multiobjective Metaheuristic for Multiple Sequence Alignment. J. Comput. Biol. 25(9): 1009-1022 (2018) - [j53]Sanjeevan Shrestha, Leonardo Vanneschi:
Improved Fully Convolutional Network with Conditional Random Fields for Building Extraction. Remote. Sens. 10(7): 1135 (2018) - [j52]Sara Silva, Leonardo Vanneschi, Ana I. R. Cabral, Maria José Alves do Rio Perestrelo de Vasconcelos:
A semi-supervised Genetic Programming method for dealing with noisy labels and hidden overfitting. Swarm Evol. Comput. 39: 323-338 (2018) - [j51]Álvaro Rubio-Largo, Leonardo Vanneschi, Mauro Castelli, Miguel A. Vega-Rodríguez:
Swarm intelligence for optimizing the parameters of multiple sequence aligners. Swarm Evol. Comput. 42: 16-28 (2018) - [j50]Álvaro Rubio-Largo, Leonardo Vanneschi, Mauro Castelli, Miguel A. Vega-Rodríguez:
A Characteristic-Based Framework for Multiple Sequence Aligners. IEEE Trans. Cybern. 48(1): 41-51 (2018) - [c109]Mauro Castelli, Ivo Gonçalves, Luca Manzoni, Leonardo Vanneschi:
Pruning Techniques for Mixed Ensembles of Genetic Programming Models. EuroGP 2018: 52-67 - [c108]Leonardo Vanneschi, Kristen M. Scott, Mauro Castelli:
A Multiple Expression Alignment Framework for Genetic Programming. EuroGP 2018: 166-183 - [c107]William G. La Cava, Sara Silva, Kourosh Danai, Lee Spector, Leonardo Vanneschi, Jason H. Moore:
A multidimensional genetic programming approach for identifying epsistatic gene interactions. GECCO (Companion) 2018: 23-24 - [c106]Palina Bartashevich, Illya Bakurov, Sanaz Mostaghim, Leonardo Vanneschi:
Evolving PSO algorithm design in vector fields using geometric semantic GP. GECCO (Companion) 2018: 262-263 - [c105]Palina Bartashevich, Illya Bakurov, Sanaz Mostaghim, Leonardo Vanneschi:
PSO-Based Search Rules for Aerial Swarms Against Unexplored Vector Fields via Genetic Programming. PPSN (1) 2018: 41-53 - [c104]Illya Bakurov, Leonardo Vanneschi, Mauro Castelli, Francesco Fontanella:
EDDA-V2 - An Improvement of the Evolutionary Demes Despeciation Algorithm. PPSN (1) 2018: 185-196 - [i6]Mauro Castelli, Ivo Gonçalves, Luca Manzoni, Leonardo Vanneschi:
Pruning Techniques for Mixed Ensembles of Genetic Programming Models. CoRR abs/1801.07668 (2018) - 2017
- [j49]Mauro Castelli, Luca Manzoni, Leonardo Vanneschi, Ales Popovic:
An expert system for extracting knowledge from customers' reviews: The case of Amazon.com, Inc. Expert Syst. Appl. 84: 117-126 (2017) - [j48]Mauro Castelli, Leonardo Vanneschi, Leonardo Trujillo, Ales Popovic:
Stock index return forecasting: semantics-based genetic programming with local search optimiser. Int. J. Bio Inspired Comput. 10(3): 159-171 (2017) - [j47]Leonardo Vanneschi, Mauro Castelli, Alessandro Re:
Prediction of ships' position by analysing AIS data: an artificial intelligence approach. Int. J. Web Eng. Technol. 12(3): 253-274 (2017) - [j46]Álvaro Rubio-Largo, Leonardo Vanneschi, Mauro Castelli, Miguel A. Vega-Rodríguez:
Using biological knowledge for multiple sequence aligner decision making. Inf. Sci. 420: 278-298 (2017) - [j45]Álvaro Rubio-Largo, Leonardo Vanneschi, Mauro Castelli, Miguel A. Vega-Rodríguez:
Reducing Alignment Time Complexity of Ultra-Large Sets of Sequences. J. Comput. Biol. 24(11): 1144-1154 (2017) - [j44]Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Vanneschi, Ales Popovic:
The influence of population size in geometric semantic GP. Swarm Evol. Comput. 32: 110-120 (2017) - [j43]Leonardo Vanneschi, Roberto Henriques, Mauro Castelli:
Multi-objective genetic algorithm with variable neighbourhood search for the electoral redistricting problem. Swarm Evol. Comput. 36: 37-51 (2017) - [c103]Leonardo Vanneschi, Illya Bakurov, Mauro Castelli:
An initialization technique for geometric semantic GP based on demes evolution and despeciation. CEC 2017: 113-120 - [c102]Leonardo Vanneschi, Bernardo Galvão:
A parallel and distributed semantic Genetic Programming system. CEC 2017: 121-128 - [c101]Leonardo Vanneschi, Mauro Castelli, Ivo Gonçalves, Luca Manzoni, Sara Silva:
Geometric semantic genetic programming for biomedical applications: A state of the art upgrade. CEC 2017: 177-184 - [c100]Carlos A. Goribar Jiménez, Yazmín Maldonado, Leonardo Trujillo, Mauro Castelli, Ivo Gonçalves, Leonardo Vanneschi:
Towards the development of a complete GP system on an FPGA using geometric semantic operators. CEC 2017: 1932-1939 - [c99]William G. La Cava, Sara Silva, Leonardo Vanneschi, Lee Spector, Jason H. Moore:
Genetic Programming Representations for Multi-dimensional Feature Learning in Biomedical Classification. EvoApplications (1) 2017: 158-173 - [c98]Leonardo Vanneschi, Mauro Castelli, Luca Manzoni, Krzysztof Krawiec, Alberto Moraglio, Sara Silva, Ivo Gonçalves:
PSXO: population-wide semantic crossover. GECCO (Companion) 2017: 257-258 - [i5]Mauro Castelli, Gianpiero Cattaneo, Luca Manzoni, Leonardo Vanneschi:
A Distance Between Populations for n-Points Crossover in Genetic Algorithms. CoRR abs/1707.00451 (2017) - 2016
- [j42]Mauro Castelli, Leonardo Trujillo, Leonardo Vanneschi, Ales Popovic:
Prediction of relative position of CT slices using a computational intelligence system. Appl. Soft Comput. 46: 537-542 (2016) - [j41]Mauro Castelli, Leonardo Vanneschi, Ales Popovic:
Controlling Individuals Growth in Semantic Genetic Programming through Elitist Replacement. Comput. Intell. Neurosci. 2016: 8326760:1-8326760:12 (2016) - [j40]Mauro Castelli, Luca Manzoni, Leonardo Vanneschi, Sara Silva, Ales Popovic:
Self-tuning geometric semantic Genetic Programming. Genet. Program. Evolvable Mach. 17(1): 55-74 (2016) - [j39]Mauro Castelli, Leonardo Vanneschi, Ales Popovic:
Parameter evaluation of geometric semantic genetic programming in pharmacokinetics. Int. J. Bio Inspired Comput. 8(1): 42-50 (2016) - [j38]Mauro Castelli, Leonardo Vanneschi, Luca Manzoni, Ales Popovic:
Semantic genetic programming for fast and accurate data knowledge discovery. Swarm Evol. Comput. 26: 1-7 (2016) - [c97]Alessandro Re, Mauro Castelli, Leonardo Vanneschi:
A Comparison Between Representations for Evolving Images. EvoMUSART 2016: 163-185 - [c96]Leonardo Trujillo, Emigdio Z.-Flores, Perla S. Juárez-Smith, Pierrick Legrand, Sara Silva, Mauro Castelli, Leonardo Vanneschi, Oliver Schütze, Luis Muñoz:
Local Search is Underused in Genetic Programming. GPTP 2016: 119-137 - [c95]Mauro Castelli, Luca Manzoni, Ivo Gonçalves, Leonardo Vanneschi, Leonardo Trujillo, Sara Silva:
An Analysis of Geometric Semantic Crossover: A Computational Geometry Approach. IJCCI (ECTA) 2016: 201-208 - 2015
- [j37]Mauro Castelli, Leonardo Trujillo, Leonardo Vanneschi:
Energy Consumption Forecasting Using Semantic-Based Genetic Programming with Local Search Optimizer. Comput. Intell. Neurosci. 2015: 971908:1-971908:8 (2015) - [j36]Mauro Castelli, Sara Silva, Leonardo Vanneschi:
A C++ framework for geometric semantic genetic programming. Genet. Program. Evolvable Mach. 16(1): 73-81 (2015) - [j35]Mauro Castelli, Roberto Henriques, Leonardo Vanneschi:
A geometric semantic genetic programming system for the electoral redistricting problem. Neurocomputing 154: 200-207 (2015) - [c94]Mauro Castelli, Matteo De Felice, Luca Manzoni, Leonardo Vanneschi:
Electricity Demand Modelling with Genetic Programming. EPIA 2015: 213-225 - [c93]Leonardo Vanneschi, Mauro Castelli, Ernesto Costa, Alessandro Re, Henrique Vaz, Victor Sousa Lobo, Paulo Urbano:
Improving Maritime Awareness with Semantic Genetic Programming and Linear Scaling: Prediction of Vessels Position Based on AIS Data. EvoApplications 2015: 732-744 - [c92]Mauro Castelli, Leonardo Trujillo, Leonardo Vanneschi, Sara Silva, Emigdio Z.-Flores, Pierrick Legrand:
Geometric Semantic Genetic Programming with Local Search. GECCO 2015: 999-1006 - [c91]Sara Silva, Luis Muñoz, Leonardo Trujillo, Vijay Ingalalli, Mauro Castelli, Leonardo Vanneschi:
Multiclass Classification Through Multidimensional Clustering. GPTP 2015: 219-239 - [c90]Leonardo Vanneschi:
An Introduction to Geometric Semantic Genetic Programming. NEO 2015: 3-42 - 2014
- [j34]Mauro Castelli, Leonardo Vanneschi, Sara Silva:
Prediction of the Unified Parkinson's Disease Rating Scale assessment using a genetic programming system with geometric semantic genetic operators. Expert Syst. Appl. 41(10): 4608-4616 (2014) - [j33]Leonardo Vanneschi, Mauro Castelli, Sara Silva:
A survey of semantic methods in genetic programming. Genet. Program. Evolvable Mach. 15(2): 195-214 (2014) - [j32]Mauro Castelli, Sara Silva, Luca Manzoni, Leonardo Vanneschi:
Geometric Selective Harmony Search. Inf. Sci. 279: 468-482 (2014) - [j31]Andrea Valsecchi, Leonardo Vanneschi, Giancarlo Mauri:
A study of search algorithms' optimization speed. J. Comb. Optim. 27(2): 256-270 (2014) - [j30]Leonardo Vanneschi:
Improving genetic programming for the prediction of pharmacokinetic parameters. Memetic Comput. 6(4): 255-262 (2014) - [j29]Mauro Castelli, Leonardo Vanneschi:
Genetic algorithm with variable neighborhood search for the optimal allocation of goods in shop shelves. Oper. Res. Lett. 42(5): 355-360 (2014) - [j28]Mauro Castelli, Leonardo Vanneschi, Sara Silva, Alexandros Agapitos, Michael O'Neill:
Semantic Search-Based Genetic Programming and the Effect of Intron Deletion. IEEE Trans. Cybern. 44(1): 103-113 (2014) - [j27]Mauro Castelli, Leonardo Vanneschi, Sara Silva:
Corrections to "Semantic Search Based Genetic Programming and the Effect of Introns Deletion". IEEE Trans. Cybern. 44(4): 565 (2014) - [c89]Vijay Ingalalli, Sara Silva, Mauro Castelli, Leonardo Vanneschi:
A Multi-dimensional Genetic Programming Approach for Multi-class Classification Problems. EuroGP 2014: 48-60 - [c88]Stefano Ruberto, Leonardo Vanneschi, Mauro Castelli, Sara Silva:
ESAGP - A Semantic GP Framework Based on Alignment in the Error Space. EuroGP 2014: 150-161 - [c87]Mauro Castelli, Leonardo Vanneschi, Sara Silva, Stefano Ruberto:
How to Exploit Alignment in the Error Space: Two Different GP Models. GPTP 2014: 133-148 - [c86]Mauro Castelli, Leonardo Vanneschi:
A hybrid Harmony search algorithm with variable neighbourhood search for the bin-packing problem. NaBIC 2014: 1-6 - [p4]Mario Giacobini, Paolo Provero, Leonardo Vanneschi, Giancarlo Mauri:
Towards the Use of Genetic Programming for the Prediction of Survival in Cancer. Evolution, Complexity and Artificial Life 2014: 177-192 - 2013
- [j26]Mauro Castelli, Leonardo Vanneschi, Sara Silva:
Prediction of high performance concrete strength using Genetic Programming with geometric semantic genetic operators. Expert Syst. Appl. 40(17): 6856-6862 (2013) - [j25]Leonardo Vanneschi, Matteo Mondini, Martino Bertoni, Alberto Ronchi, Mattia Stefano:
Gene regulatory networks reconstruction from time series datasets using genetic programming: a comparison between tree-based and graph-based approaches. Genet. Program. Evolvable Mach. 14(4): 431-455 (2013) - [j24]Luca Manzoni, Mauro Castelli, Leonardo Vanneschi:
A new genetic programming framework based on reaction systems. Genet. Program. Evolvable Mach. 14(4): 457-471 (2013) - [j23]Mauro Castelli, Stefano Beretta, Leonardo Vanneschi:
A hybrid genetic algorithm for the repetition free longest common subsequence problem. Oper. Res. Lett. 41(6): 644-649 (2013) - [c85]Mauro Castelli, Davide Castaldi, Ilaria Giordani, Sara Silva, Leonardo Vanneschi, Francesco Archetti, Daniele Maccagnola:
An Efficient Implementation of Geometric Semantic Genetic Programming for Anticoagulation Level Prediction in Pharmacogenetics. EPIA 2013: 78-89 - [c84]Leonardo Vanneschi, Mauro Castelli, Luca Manzoni, Sara Silva:
A New Implementation of Geometric Semantic GP and Its Application to Problems in Pharmacokinetics. EuroGP 2013: 205-216 - [c83]Mauro Castelli, Sara Silva, Leonardo Vanneschi, Ana I. R. Cabral, Maria J. P. de Vasconcelos, Luís Catarino, João Manuel de Brito Carreiras:
Land Cover/Land Use Multiclass Classification Using GP with Geometric Semantic Operators. EvoApplications 2013: 334-343 - [c82]Sara Silva, Vijay Ingalalli, Susana Vinga, João Manuel de Brito Carreiras, Joana B. Melo, Mauro Castelli, Leonardo Vanneschi, Ivo Gonçalves, José Caldas:
Prediction of Forest Aboveground Biomass: An Exercise on Avoiding Overfitting. EvoApplications 2013: 407-417 - [c81]Mauro Castelli, Davide Castaldi, Leonardo Vanneschi, Ilaria Giordani, Francesco Archetti, Daniele Maccagnola:
An efficient implementation of geometric semantic genetic programming for anticoagulation level prediction in pharmacogenetics. GECCO (Companion) 2013: 137-138 - [c80]Leonardo Vanneschi, Sara Silva, Mauro Castelli, Luca Manzoni:
Geometric Semantic Genetic Programming for Real Life Applications. GPTP 2013: 191-209 - [e5]Leonardo Vanneschi, William S. Bush, Mario Giacobini:
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 11th European Conference, EvoBIO 2013, Vienna, Austria, April 3-5, 2013. Proceedings. Lecture Notes in Computer Science 7833, Springer 2013, ISBN 978-3-642-37188-2 [contents] - 2012
- [j22]Sara Silva, Stephen Dignum, Leonardo Vanneschi:
Operator equalisation for bloat free genetic programming and a survey of bloat control methods. Genet. Program. Evolvable Mach. 13(2): 197-238 (2012) - [j21]Sara Silva, Leonardo Vanneschi:
Bloat free genetic programming: application to human oral bioavailability prediction. Int. J. Data Min. Bioinform. 6(6): 585-601 (2012) - [j20]Leonardo Vanneschi, Giancarlo Mauri:
A study on learning robustness using asynchronous 1D cellular automata rules. Nat. Comput. 11(2): 289-302 (2012) - [j19]Leonardo Vanneschi, Yuri Pirola, Giancarlo Mauri, Marco Tomassini, Philippe Collard, Sébastien Vérel:
A study of the neutrality of Boolean function landscapes in genetic programming. Theor. Comput. Sci. 425: 34-57 (2012) - [j18]Luca Manzoni, Leonardo Vanneschi, Giancarlo Mauri:
A distance between populations for one-point crossover in genetic algorithms. Theor. Comput. Sci. 429: 213-221 (2012) - [c79]Luca Manzoni, Mauro Castelli, Leonardo Vanneschi:
Evolutionary Reaction Systems. EvoBIO 2012: 13-25 - [c78]Leonardo Vanneschi, Matteo Mondini, Martino Bertoni, Alberto Ronchi, Mattia Stefano:
GeNet: A Graph-Based Genetic Programming Framework for the Reverse Engineering of Gene Regulatory Networks. EvoBIO 2012: 97-109 - [c77]Mauro Castelli, Luca Manzoni, Leonardo Vanneschi:
Parameter tuning of evolutionary reactions systems. GECCO 2012: 727-734 - [c76]James McDermott, David Robert White, Sean Luke, Luca Manzoni, Mauro Castelli, Leonardo Vanneschi, Wojciech Jaskowski, Krzysztof Krawiec, Robin Harper, Kenneth A. De Jong, Una-May O'Reilly:
Genetic programming needs better benchmarks. GECCO 2012: 791-798 - [p3]Leonardo Vanneschi, Riccardo Poli:
Genetic Programming - Introduction, Applications, Theory and Open Issues. Handbook of Natural Computing 2012: 709-739 - [p2]Leonardo Vanneschi, Daniele Codecasa, Giancarlo Mauri:
An Empirical Study of Parallel and Distributed Particle Swarm Optimization. Parallel Architectures and Bioinspired Algorithms 2012: 125-150 - [e4]Mario Giacobini, Leonardo Vanneschi, William S. Bush:
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 10th European Conference, EvoBIO 2012, Málaga, Spain, April 11-13, 2012. Proceedings. Lecture Notes in Computer Science 7246, Springer 2012, ISBN 978-3-642-29065-7 [contents] - [i4]Mauro Castelli, Luca Manzoni, Leonardo Vanneschi:
An Efficient Genetic Programming System with Geometric Semantic Operators and its Application to Human Oral Bioavailability Prediction. CoRR abs/1208.2437 (2012) - 2011
- [j17]Leonardo Vanneschi, Antonella Farinaccio, Giancarlo Mauri, Marco Antoniotti, Paolo Provero, Mario Giacobini:
A comparison of machine learning techniques for survival prediction in breast cancer. BioData Min. 4: 12 (2011) - [j16]Leonardo Vanneschi, Luca Mussi, Stefano Cagnoni:
Hot topics in Evolutionary Computation. Intelligenza Artificiale 5(1): 5-17 (2011) - [j15]Leonardo Vanneschi, Daniele Codecasa, Giancarlo Mauri:
A Comparative Study of Four Parallel and Distributed PSO Methods. New Gener. Comput. 29(2): 129-161 (2011) - [c75]Mauro Castelli, Luca Manzoni, Leonardo Vanneschi:
A Method to Reuse Old Populations in Genetic Algorithms. EPIA 2011: 138-152 - [c74]Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Vanneschi:
A Quantitative Study of Learning and Generalization in Genetic Programming. EuroGP 2011: 25-36 - [c73]James McDermott, Una-May O'Reilly, Leonardo Vanneschi, Kalyan Veeramachaneni:
How Far Is It from Here to There? A Distance That Is Coherent with GP Operators. EuroGP 2011: 190-202 - [c72]Leonardo Trujillo, Sara Silva, Pierrick Legrand, Leonardo Vanneschi:
An Empirical Study of Functional Complexity as an Indicator of Overfitting in Genetic Programming. EuroGP 2011: 262-273 - [c71]Antonella Farinaccio, Leonardo Vanneschi, Paolo Provero, Giancarlo Mauri, Mario Giacobini:
A New Evolutionary Gene Regulatory Network Reverse Engineering Tool. EvoBio 2011: 13-24 - [c70]Mauro Castelli, Luca Manzoni, Leonardo Vanneschi:
The effect of selection from old populations in genetic algorithms. GECCO (Companion) 2011: 161-162 - [c69]Leonardo Vanneschi, Mauro Castelli, Luca Manzoni:
The K landscapes: a tunably difficult benchmark for genetic programming. GECCO 2011: 1467-1474 - [c68]Mauro Castelli, Luca Manzoni, Leonardo Vanneschi:
Multi Objective Genetic Programming for Feature Construction in Classification Problems. LION 2011: 503-506 - [p1]Stefano Cagnoni, Leonardo Vanneschi:
Evolutionary Computation: A Brief Overview. Genetic and Evolutionary Computation: Medical Applications 2011 - [i3]Leonardo Vanneschi, Sébastien Vérel, Philippe Collard, Marco Tomassini:
NK landscapes difficulty and Negative Slope Coefficient: How Sampling Influences the Results. CoRR abs/1107.4164 (2011) - 2010
- [j14]Francesco Archetti, Ilaria Giordani, Leonardo Vanneschi:
Genetic programming for QSAR investigation of docking energy. Appl. Soft Comput. 10(1): 170-182 (2010) - [j13]Francesco Archetti, Ilaria Giordani, Leonardo Vanneschi:
Genetic programming for anticancer therapeutic response prediction using the NCI-60 dataset. Comput. Oper. Res. 37(8): 1395-1405 (2010) - [j12]Marco Tomassini, Leonardo Vanneschi:
Guest editorial: special issue on parallel and distributed evolutionary algorithms, part two. Genet. Program. Evolvable Mach. 11(2): 129-130 (2010) - [j11]Riccardo Poli, Leonardo Vanneschi, William B. Langdon, Nicholas Freitag McPhee:
Theoretical results in genetic programming: the next ten years? Genet. Program. Evolvable Mach. 11(3-4): 285-320 (2010) - [j10]Michael O'Neill, Leonardo Vanneschi, Steven M. Gustafson, Wolfgang Banzhaf:
Open issues in genetic programming. Genet. Program. Evolvable Mach. 11(3-4): 339-363 (2010) - [c67]Andrea Valsecchi, Leonardo Vanneschi, Giancarlo Mauri:
A Study on the Automatic Generation of Asynchronous Cellular Automata Rules by Means of Genetic Algorithms. ACRI 2010: 429-438 - [c66]Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Vanneschi:
A comparison of the generalization ability of different genetic programming frameworks. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c65]Leonardo Vanneschi, Antonella Farinaccio, Mario Giacobini, Giancarlo Mauri, Marco Antoniotti, Paolo Provero:
Identification of Individualized Feature Combinations for Survival Prediction in Breast Cancer: A Comparison of Machine Learning Techniques. EvoBIO 2010: 110-121 - [c64]Leonardo Vanneschi, Mauro Castelli, Simone Bianco, Raimondo Schettini:
Genetic Algorithms for Training Data and Polynomial Optimization in Colorimetric Characterization of Scanners. EvoApplications (1) 2010: 282-291 - [c63]Leonardo Vanneschi, Daniele Codecasa, Giancarlo Mauri:
An empirical comparison of parallel and distributed particle swarm optimization methods. GECCO 2010: 15-22 - [c62]Antonella Farinaccio, Leonardo Vanneschi, Mario Giacobini, Giancarlo Mauri, Paolo Provero:
On the use of genetic programming for the prediction of survival in cancer. GECCO 2010: 163-170 - [c61]Leonardo Vanneschi, Mauro Castelli, Sara Silva:
Measuring bloat, overfitting and functional complexity in genetic programming. GECCO 2010: 877-884 - [c60]Luca Manzoni, Leonardo Vanneschi, Giancarlo Mauri:
Definition of a crossover based distance for genetic algorithms. GECCO 2010: 1473-1474 - [c59]Andrea Valsecchi, Leonardo Vanneschi, Giancarlo Mauri:
Optimization speed and fair sets of functions. GECCO 2010: 1475-1476 - [c58]Leonardo Vanneschi:
Fitness landscapes and problem hardness in genetic programming. GECCO (Companion) 2010: 2711-2738 - [c57]Leonardo Vanneschi, Daniele Codecasa, Giancarlo Mauri:
A study of parallel and distributed particle swarm optimization methods. BADS@ICAC 2010: 9-16 - [c56]Sara Silva, Leonardo Vanneschi:
State-of-the-Art Genetic Programming for Predicting Human Oral Bioavailability of Drugs. IWPACBB 2010: 165-173 - [c55]Antonella Farinaccio, Leonardo Vanneschi, Paolo Provero, Giancarlo Mauri, Mario Giacobini:
A Study on Gene Regulatory Network Reconstruction and Simulation. WIRN 2010: 235-242
2000 – 2009
- 2009
- [j9]Marco Tomassini, Leonardo Vanneschi:
Introduction: special issue on parallel and distributed evolutionary algorithms, part I. Genet. Program. Evolvable Mach. 10(4): 339-341 (2009) - [j8]Stefania Bandini, Leonardo Vanneschi, Andrew Wuensche, Alessandro Bahgat Shehata:
Cellular Automata Pattern Recognition and Rule Evolution Through a Neuro-Genetic Approach. J. Cell. Autom. 4(3): 171-181 (2009) - [c54]Leonardo Vanneschi, Sara Silva:
Using Operator Equalisation for Prediction of Drug Toxicity with Genetic Programming. EPIA 2009: 65-76 - [c53]Daniela Besozzi, Paolo Cazzaniga, Giancarlo Mauri, Dario Pescini, Leonardo Vanneschi:
A Comparison of Genetic Algorithms and Particle Swarm Optimization for Parameter Estimation in Stochastic Biochemical Systems. EvoBIO 2009: 116-127 - [c52]Leonardo Vanneschi, Sébastien Vérel, Marco Tomassini, Philippe Collard:
NK Landscapes Difficulty and Negative Slope Coefficient: How Sampling Influences the Results. EvoWorkshops 2009: 645-654 - [c51]Sara Silva, Leonardo Vanneschi:
Operator equalisation, bloat and overfitting: a study on human oral bioavailability prediction. GECCO 2009: 1115-1122 - [c50]Leonardo Vanneschi, Steven M. Gustafson:
Using crossover based similarity measure to improve genetic programming generalization ability. GECCO 2009: 1139-1146 - [c49]Leonardo Vanneschi, Andrea Valsecchi, Riccardo Poli:
Limitations of the fitness-proportional negative slope coefficient as a difficulty measure. GECCO 2009: 1877-1878 - [c48]Leonardo Vanneschi, Giuseppe Cuccu:
Variable size population for dynamic optimization with genetic programming. GECCO 2009: 1895-1896 - [c47]Leonardo Vanneschi:
Fitness landscapes and problem hardness in genetic programming. GECCO (Companion) 2009: 3657-3684 - [c46]Simone Bianco, Raimondo Schettini, Leonardo Vanneschi:
Empirical modeling for colorimetric characterization of digital cameras. ICIP 2009: 3469-3472 - [c45]Leonardo Vanneschi, Giuseppe Cuccu:
A Study of Genetic Programming Variable Population Size for Dynamic Optimization Problems. IJCCI 2009: 119-126 - [e3]Leonardo Vanneschi, Steven M. Gustafson, Alberto Moraglio, Ivanoe De Falco, Marc Ebner:
Genetic Programming, 12th European Conference, EuroGP 2009, Tübingen, Germany, April 15-17, 2009, Proceedings. Lecture Notes in Computer Science 5481, Springer 2009, ISBN 978-3-642-01180-1 [contents] - 2008
- [j7]Stefania Bandini, Leonardo Vanneschi, Andrew Wuensche, Alessandro Bahgat Shehata:
A Neuro-Genetic Framework for Pattern Recognition in Complex Systems. Fundam. Informaticae 87(2): 207-226 (2008) - [j6]Simone Bianco, Francesca Gasparini, Raimondo Schettini, Leonardo Vanneschi:
Polynomial modeling and optimization for colorimetric characterization of scanners. J. Electronic Imaging 17(4): 043002 (2008) - [j5]Steven M. Gustafson, Leonardo Vanneschi:
Crossover-Based Tree Distance in Genetic Programming. IEEE Trans. Evol. Comput. 12(4): 506-524 (2008) - [c44]Stefania Bandini, Sara Manzoni, Giancarlo Mauri, Stefano Redaelli, Leonardo Vanneschi:
GP Generation of Pedestrian Behavioral Rules in an Evacuation Model Based on SCA. ACRI 2008: 409-416 - [c43]Stefania Bandini, Sara Manzoni, Leonardo Vanneschi:
Evolving robust cellular automata rules with genetic programming. Automata 2008: 542-556 - [c42]Simone Bianco, Francesca Gasparini, Raimondo Schettini, Leonardo Vanneschi:
An Evolutionary Framework for Colorimetric Characterization of Scanners. EvoWorkshops 2008: 245-254 - [c41]Stefano Cagnoni, Leonardo Vanneschi, Antonia Azzini, Andrea Tettamanzi:
A Critical Assessment of Some Variants of Particle Swarm Optimization. EvoWorkshops 2008: 565-574 - [c40]Andrea Valsecchi, Leonardo Vanneschi:
A Study of Some Implications of the No Free Lunch Theorem. EvoWorkshops 2008: 633-642 - [c39]Marco Tomassini, Leonardo Vanneschi:
Negative Slope Coefficient and the Difficulty of Random 3-SAT Instances. EvoWorkshops 2008: 643-648 - [c38]Riccardo Poli, Nicholas Freitag McPhee, Leonardo Vanneschi:
The impact of population size on code growth in GP: analysis and empirical validation. GECCO 2008: 1275-1282 - [c37]Riccardo Poli, Nicholas Freitag McPhee, Leonardo Vanneschi:
Elitism reduces bloat in genetic programming. GECCO 2008: 1343-1344 - [e2]Michael O'Neill, Leonardo Vanneschi, Steven M. Gustafson, Anna Esparcia-Alcázar, Ivanoe De Falco, Antonio Della Cioppa, Ernesto Tarantino:
Genetic Programming, 11th European Conference, EuroGP 2008, Naples, Italy, March 26-28, 2008. Proceedings. Lecture Notes in Computer Science 4971, Springer 2008, ISBN 978-3-540-78670-2 [contents] - [i2]Sébastien Vérel, Philippe Collard, Marco Tomassini, Leonardo Vanneschi:
Neutral Fitness Landscape in the Cellular Automata Majority Problem. CoRR abs/0803.4240 (2008) - 2007
- [j4]Francesco Archetti, Stefano Lanzeni, Enza Messina, Leonardo Vanneschi:
Genetic programming for computational pharmacokinetics in drug discovery and development. Genet. Program. Evolvable Mach. 8(4): 413-432 (2007) - [j3]Sébastien Vérel, Philippe Collard, Marco Tomassini, Leonardo Vanneschi:
Fitness landscape of the cellular automata majority problem: View from the "Olympus". Theor. Comput. Sci. 378(1): 54-77 (2007) - [c36]Leonardo Vanneschi, Marco Tomassini, Philippe Collard, Sébastien Vérel, Yuri Pirola, Giancarlo Mauri:
A Comprehensive View of Fitness Landscapes with Neutrality and Fitness Clouds. EuroGP 2007: 241-250 - [c35]Francesco Archetti, Stefano Lanzeni, Enza Messina, Leonardo Vanneschi:
Genetic Programming and Other Machine Learning Approaches to Predict Median Oral Lethal Dose (LD50) and Plasma Protein Binding Levels (%PPB) of Drugs. EvoBIO 2007: 11-23 - [c34]Riccardo Poli, Leonardo Vanneschi:
Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms. GECCO 2007: 1335-1342 - [c33]Leonardo Vanneschi, Denis Rochat, Marco Tomassini:
Multi-optimization improves genetic programming generalization ability. GECCO 2007: 1759 - [c32]Leonardo Vanneschi, Sébastien Vérel:
Fitness landscapes and problem hardness in evolutionary computation. GECCO (Companion) 2007: 3690-3733 - [e1]Marc Ebner, Michael O'Neill, Anikó Ekárt, Leonardo Vanneschi, Anna Esparcia-Alcázar:
Genetic Programming, 10th European Conference, EuroGP 2007, Valencia, Spain, April 11-13, 2007, Proceedings. Lecture Notes in Computer Science 4445, Springer 2007, ISBN 978-3-540-71602-0 [contents] - [i1]Sébastien Vérel, Philippe Collard, Marco Tomassini, Leonardo Vanneschi:
Fitness landscape of the cellular automata majority problem: View from the Olympus. CoRR abs/0709.3974 (2007) - 2006
- [c31]Sébastien Vérel, Philippe Collard, Marco Tomassini, Leonardo Vanneschi:
Neutral Fitness Landscape in the Cellular Automata Majority Problem. ACRI 2006: 258-267 - [c30]Stefania Bandini, Sara Manzoni, Stefano Redaelli, Leonardo Vanneschi:
Automatic Detection of Go-Based Patterns in CA Model of Vegetable Populations: Experiments on Geta Pattern Recognition. ACRI 2006: 427-435 - [c29]Leonardo Vanneschi, Marco Tomassini, Philippe Collard, Sébastien Vérel:
Negative Slope Coefficient: A Measure to Characterize Genetic Programming Fitness Landscapes. EuroGP 2006: 178-189 - [c28]Leonardo Vanneschi, Steven M. Gustafson, Giancarlo Mauri:
Using Subtree Crossover Distance to Investigate Genetic Programming Dynamics. EuroGP 2006: 238-249 - [c27]Francesco Archetti, Enza Messina, Daniele Toscani, Leonardo Vanneschi:
Classifying and Counting Vehicles in Traffic Control Applications. EvoWorkshops 2006: 495-499 - [c26]Francesco Archetti, Stefano Lanzeni, Enza Messina, Leonardo Vanneschi:
Genetic programming for human oral bioavailability of drugs. GECCO 2006: 255-262 - [c25]Leonardo Vanneschi, Giancarlo Mauri, Andrea Valsecchi, Stefano Cagnoni:
Heterogeneous cooperative coevolution: strategies of integration between GP and GA. GECCO 2006: 361-368 - [c24]Leonardo Vanneschi, Yuri Pirola, Philippe Collard:
A quantitative study of neutrality in GP boolean landscapes. GECCO 2006: 895-902 - [c23]Stefania Bandini, Sara Manzoni, Stefano Redaelli, Leonardo Vanneschi:
Emergent Spatial Patterns in Vegetable Population Dynamics: Towards Pattern Detection and Interpretation. International Conference on Computational Science (3) 2006: 289-296 - 2005
- [j2]Marco Tomassini, Leonardo Vanneschi, Philippe Collard, Manuel Clergue:
A Study of Fitness Distance Correlation as a Difficulty Measure in Genetic Programming. Evol. Comput. 13(2): 213-239 (2005) - [c22]Leonardo Vanneschi, Marco Tomassini, Philippe Collard, Manuel Clergue:
A Survey of Problem Difficulty in Genetic Programming. AI*IA 2005: 66-77 - [c21]Stefano Cagnoni, Daniel Rivero, Leonardo Vanneschi:
A purely evolutionary memetic algorithm as a first step towards symbiotic coevolution. Congress on Evolutionary Computation 2005: 1156-1163 - [c20]Denis Rochat, Marco Tomassini, Leonardo Vanneschi:
Dynamic Size Populations in Distributed Genetic Programming. EuroGP 2005: 50-61 - [c19]Steven M. Gustafson, Leonardo Vanneschi:
Operator-Based Distance for Genetic Programming: Subtree Crossover Distance. EuroGP 2005: 178-189 - 2004
- [c18]Marco Tomassini, Leonardo Vanneschi, Jerome Cuendet, Francisco Fernández:
A new technique for dynamic size populations in genetic programming. IEEE Congress on Evolutionary Computation 2004: 486-493 - [c17]Leonardo Vanneschi, Manuel Clergue, Philippe Collard, Marco Tomassini, Sébastien Vérel:
Fitness Clouds and Problem Hardness in Genetic Programming. GECCO (2) 2004: 690-701 - 2003
- [j1]Francisco Fernández, Marco Tomassini, Leonardo Vanneschi:
An Empirical Study of Multipopulation Genetic Programming. Genet. Program. Evolvable Mach. 4(1): 21-51 (2003) - [c16]Marco Tomassini, Leonardo Vanneschi, Francisco Fernández, Germán Galeano Gil:
A Study of Diversity in Multipopulation Genetic Programming. Artificial Evolution 2003: 243-255 - [c15]Leonardo Vanneschi, Marco Tomassini, Philippe Collard, Manuel Clergue:
Fitness distance correlation in genetic programming: a constructive counterexample. IEEE Congress on Evolutionary Computation 2003: 289-296 - [c14]Gianluigi Folino, Clara Pizzuti, Giandomenico Spezzano, Leonardo Vanneschi, Marco Tomassini:
Diversity analysis in cellular and multipopulation genetic programming. IEEE Congress on Evolutionary Computation 2003: 305-311 - [c13]Francisco Fernández, Marco Tomassini, Leonardo Vanneschi:
Saving computational effort in genetic programming by means of plagues. IEEE Congress on Evolutionary Computation 2003: 2042-2049 - [c12]Francisco Fernández, Leonardo Vanneschi, Marco Tomassini:
The Effect of Plagues in Genetic Programming: A Study of Variable-Size Populations. EuroGP 2003: 317-326 - [c11]Leonardo Vanneschi, Marco Tomassini, Philippe Collard, Manuel Clergue:
Fitness Distance Correlation in Structural Mutation Genetic Programming. EuroGP 2003: 455-464 - [c10]Leonardo Vanneschi, Marco Tomassini, Manuel Clergue, Philippe Collard:
Difficulty of Unimodal and Multimodal Landscapes in Genetic Programming. GECCO 2003: 1788-1799 - [c9]Marco Tomassini, Leonardo Vanneschi, Francisco Fernández, Germán Galeano Gil:
Diversity in Multipopulation Genetic Programming. GECCO 2003: 1812-1813 - 2002
- [c8]Germán Galeano Gil, Francisco Fernández, Marco Tomassini, Leonardo Vanneschi:
Studying the influence of synchronous and asynchronous parallel GP on programs length evolution. IEEE Congress on Evolutionary Computation 2002: 1727-1732 - [c7]Manuel Clergue, Philippe Collard, Marco Tomassini, Leonardo Vanneschi:
Fitness Distance Correlation And Problem Difficulty For Genetic Programming. GECCO 2002: 724-732 - [c6]Mario Giacobini, Marco Tomassini, Leonardo Vanneschi:
How Statistics Can Help In Limiting The Number Of Fitness Cases In Genetic Programming. GECCO 2002: 889 - [c5]Mario Giacobini, Marco Tomassini, Leonardo Vanneschi:
Limiting the Number of Fitness Cases in Genetic Programming Using Statistics. PPSN 2002: 371-380 - [c4]Marco Tomassini, Leonardo Vanneschi, Francisco Fernández, Germán Galeano Gil:
Experimental Investigation of Three Distributed Genetic Programming Models. PPSN 2002: 641-650 - 2001
- [c3]Francisco Fernández, Marco Tomassini, Leonardo Vanneschi:
Studying the Influence of Communication Topology and Migration on Distributed Genetic Programming. EuroGP 2001: 51-63 - 2000
- [c2]Marco Tomassini, Leonardo Vanneschi, Laurent Bucher, Francisco Fernández:
An MPI-Based Tool for Distributed Genetic Programming. CLUSTER 2000: 209-216 - [c1]Francisco Fernández, Marco Tomassini, Leonardo Vanneschi, Laurent Bucher:
A Distributed Computing Environment for Genetic Programming Using MPI. PVM/MPI 2000: 322-329
Coauthor Index
[j90] [c135] [j83] [j80] [j79] [j74] [c124] [j73] [j71] [j68] [j67] [j66] [j65] [c117] [c116] [j63] [j62] [j60] [j59] [j58] [j57] [c112] [c111] [c110] [r3] [r2] [r1] [j56] [j55] [j54] [j51] [j50] [c109] [c108] [c104] [i6] [j49] [j48] [j47] [j46] [j45] [j44] [j43] [c103] [c101] [c100] [c98] [i5] [j42] [j41] [j40] [j39] [j38] [c97] [c96] [c95] [j37] [j36] [j35] [c94] [c93] [c92] [c91] [j34] [j33] [j32] [j29] [j28] [j27] [c89] [c88] [c87] [c86] [j26] [j24] [j23] [c85] [c84] [c83] [c82] [c81] [c80] [c79] [c77] [c76] [i4] [c75] [c74] [c70] [c69] [c68] [c66] [c64] [c61]
[j92] [j91] [j90] [j89] [j87] [c136] [b1] [c132] [c131] [c130] [c129] [j77] [c127] [j72] [i8] [j70] [j69] [j66] [c119] [c117] [c115] [i7] [j62] [j61] [c113] [j52] [c107] [j44] [c101] [c99] [c98] [j40] [c96] [c95] [j36] [c92] [c91] [j34] [j33] [j32] [j28] [j27] [c89] [c88] [c87] [j26] [c85] [c84] [c83] [c82] [c80] [j22] [j21] [c74] [c72] [c66] [c61] [c56] [c54] [c51]
Maria J. P. de Vasconcelos
aka: Maria José Alves do Rio Perestrelo de Vasconcelos
aka: Maria José Alves do Rio Perestrelo de Vasconcelos
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last updated on 2024-10-21 20:29 CEST by the dblp team
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