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Disambiguation of "Virgolin, Marco"

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On genetic programming representations and fitness functions for interpretable dimensionality reduction.

, , , and . GECCO, page 458-466. ACM, (2022)

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Monika Marcotty

Johannes Marcour

Hans-Ernst Marcolin

Carlos Javier Marcos Navas

Massimiliano Marcon

 

Other publications of authors with the same name

Model learning with personalized interpretability estimation (ML-PIE)., , , , and . GECCO Companion, page 1355-1364. ACM, (2021)Evolvability degeneration in multi-objective genetic programming for symbolic regression., , , and . GECCO, page 973-981. ACM, (2022)Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 15655-15668. PMLR, (2023)Local Search is a Remarkably Strong Baseline for Neural Architecture Search., , , and . CoRR, (2020)DAISY: An Implementation of Five Core Principles for Transparent and Accountable Conversational AI., and . Int. J. Hum. Comput. Interact., 39 (9): 1856-1873 (May 2023)An Analysis of the Ingredients for Learning Interpretable Symbolic Regression Models with Human-in-the-loop and Genetic Programming., , , , and . ACM Trans. Evol. Learn. Optim., 4 (1): 5:1-5:30 (March 2024)Scalable genetic programming by gene-pool optimal mixing and input-space entropy-based building-block learning., , , and . GECCO, page 1041-1048. ACM, (2017)Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors., , , , and . GECCO, page 1395-1402. ACM, (2018)The five Is: Key principles for interpretable and safe conversational AI., and . CIIS, page 50-54. ACM, (2021)Coefficient mutation in the gene-pool optimal mixing evolutionary algorithm for symbolic regression., and . GECCO Companion, page 2289-2297. ACM, (2022)