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Teaching Staff

Biography

Researcher, lecturer, PhD.

Scientific Publications

Bakurov, I., Buzzelli, M., Schettini, R., Castelli, M., & Vanneschi, L. (2022)

Structural similarity index (SSIM) revisited: A data-driven approach. Expert Systems with Applications, 189, 1-19. [116087]. [Advanced online publication on 27 October 2021]. https://doi.org/10.1016/j.eswa.2021.116087

Bakurov, I., Castelli, M., Fontanella, F., Scotto Di Freca, A., & Vanneschi, L. (2022)

A novel binary classification approach based on geometric semantic genetic programming. Swarm and Evolutionary Computation, 69(March), 1-12. [101028]. https://doi.org/10.1016/j.swevo.2021.101028

Bakurov, I., Buzzelli, M., Castelli, M., Schettini, R., & Vanneschi, L. (2022)

Genetic programming for structural similarity design at multiple spatial scales. In GECCO ’22. Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 911-919). (GECCO 2022 - The Genetic and Evolutionary Computation Conference, July 9-13, Boston, USA). Association for Computing Machinery (ACM). ISBN 978-1-4503-9237-2/22/07

Bakurov, I., Buzzelli, M., Castelli, M., Vanneschi, L., & Schettini, R. (2021)

General purpose optimization library (Gpol): A flexible and efficient multi-purpose optimization library in python. Applied Sciences (Switzerland), 11(11), 1-34. [4774]. https://doi.org/10.3390/app11114774

Bakurov, I; Castelli, M.; Gau, O; Fontanella, F. & Vanneschi, L. (2021)

Genetic Programming for Stacked Generalization. Swarm and Evolutionary Computation, 100913. [Advanced online publication on 26 may 2021]. https://doi.org/10.1016/j.swevo.2021.100913.

Bakurov, I., & Culotta, F. (2021)

Unemployment dynamics in Italy: a counterfactual analysis at Covid time. In B. Bertaccini, L. Fabbris, & A. Petrucci (Eds.), ASA 2021 Statistics and Information Systems for Policy Evaluation: BOOK OF SHORT PAPERS of the on-site conference (pp. 215-220). (Proceedings e report; Vol. 132). Firenze University Press. https://doi.org/10.36253/978-88-5518-461-8.40

Azzali, I., Vanneschi, L., Bakurov, I., Silva, S., Ivaldi, M., & Giacobini, M. (2020)

Towards the use of vector based GP to predict physiological time series. Applied Soft Computing Journal, 89(April), [106097]. https://doi.org/10.1016/j.asoc.2020.106097

Bakurov, I., Buzzelli, M., Castelli, M., Schettini, R., & Vanneschi, L. (2020)

Parameters optimization of the Structural Similarity Index. In London Imaging Meeting 2020: Future Colour Imaging (1 ed., Vol. 2020, pp. 19-23). (London Imaging Meeting). https://doi.org/10.2352/issn.2694-118X.2020.LIM-13

Azzali, I., Vanneschi, L., Silva, S., Bakurov, I., & Giacobini, M. (2019)

A Vectorial Approach to Genetic Programming. In N. Lourenço, T. Hu, H. Richter, L. Sekanina, & P. García-Sánchez (Eds.), Genetic Programming: 22nd  European Conference, EuroGP 2019, Held as Part of EvoStar 2019, Proceedings (pp. 213-227). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11451 LNCS). Switzerland: Springer Verlag. https://doi.org/10.1007/978-3-030-16670-0_14

Bakurov, I., Castelli, M., Fontanella, F., & Vanneschi, L. (2019)

A regression-like classification system for geometric semantic genetic programming. In J. J. Merelo, J. Garibaldi, A. Linares-Barranco, K. Madani, K. Warwick, & K. Warwick (Eds.), Proceedings of the 11th  International Joint Conference on Computational Intelligence (IJCCI 2019) (Vol. 1, pp. 40-48). (IJCCI 2019 - Proceedings of the 11th  International Joint Conference on Computational Intelligence). SciTePress.

Bakurov, I., Castelli, M., Vanneschi, L., & Freitas, M. J. (2019)

Supporting medical decisions for treating rare diseases through genetic programming. In P. Kaufmann, & P. A. Castillo (Eds.), Applications of Evolutionary Computation: 22nd  International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings (pp. 187-203). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11454 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-16692-2_13. ISBN: 978-3-030-16691-5; Online ISBN: 978-3-030-16692-2

Bartashevich, P., Bakurov, I., Mostaghim, S., & Vanneschi, L. (2018)

PSO-based search rules for aerial swarms against unexplored vector fields via genetic programming. In Parallel Problem Solving from Nature – PPSN XV: 15th  International Conference, 2018, Proceedings (pp. 41-53). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11101 LNCS). [15th  International Conference on Parallel Problem Solving from Nature, PPSN 2018, 8 to 12 september 2018, Coimbra, Portugal] Springer Verlag. DOI: 10.1007/978-3-319-99253-2_4

Bartashevich, P., Mostaghim, S., Bakurov, I., & Vanneschi, L. (2018)

Evolving PSO algorithm design in vector fields using geometric semantic GP. In GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion (pp. 262-263). New York: Association for Computing Machinery, Inc. DOI: 10.1145/3205651.3205760

Vanneschi, L., Bakurov, I., & Castelli, M. (2017)

An initialization technique for geometric semantic GP based on demes evolution and despeciation. In 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings (pp. 113-120). [7969303] Institute of Electrical and Electronics Engineers Inc.. DOI: 10.1109/CEC.2017.7969303