Marco Virgolin
Orcid: 0000-0001-8905-9313
According to our database1,
Marco Virgolin
authored at least 35 papers
between 2015 and 2024.
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Bibliography
2024
An Analysis of the Ingredients for Learning Interpretable Symbolic Regression Models with Human-in-the-loop and Genetic Programming.
ACM Trans. Evol. Learn. Optim., March, 2024
An interpretable method for automated classification of spoken transcripts and written text.
Evol. Intell., 2024
2023
DAISY: An Implementation of Five Core Principles for Transparent and Accountable Conversational AI.
Int. J. Hum. Comput. Interact., May, 2023
Artif. Intell., March, 2023
Interpretable Symbolic Regression for Data Science: Analysis of the 2022 Competition.
CoRR, 2023
Proceedings of the International Conference on Machine Learning, 2023
Mini-Batching, Gradient-Clipping, First- versus Second-Order: What Works in Gradient-Based Coefficient Optimisation for Symbolic Regression?
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
2022
Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning.
CoRR, 2022
Adults as Augmentations for Children in Facial Emotion Recognition with Contrastive Learning.
CoRR, 2022
CoRR, 2022
Coefficient mutation in the gene-pool optimal mixing evolutionary algorithm for symbolic regression.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
On genetic programming representations and fitness functions for interpretable dimensionality reduction.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022
Evolvability degeneration in multi-objective genetic programming for symbolic regression.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022
2021
Improving Model-Based Genetic Programming for Symbolic Regression of Small Expressions.
Evol. Comput., 2021
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Proceedings of the Fifth IEEE International Conference on Robotic Computing, 2021
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
Proceedings of the Evolutionary Multi-Criterion Optimization, 2021
Proceedings of the CIIS 2021: The 4th International Conference on Computational Intelligence and Intelligent Systems, Tokyo, Japan, November 20, 2021
2020
Design and Application of Gene-pool Optimal Mixing Evolutionary Algorithms for Genetic Programming.
PhD thesis, 2020
Swarm Evol. Comput., 2020
Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy.
CoRR, 2020
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020
2019
Machine learning for automatic construction of pseudo-realistic pediatric abdominal phantoms.
CoRR, 2019
A Model-based Genetic Programming Approach for Symbolic Regression of Small Expressions.
CoRR, 2019
Linear scaling with and within semantic backpropagation-based genetic programming for symbolic regression.
Proceedings of the Genetic and Evolutionary Computation Conference, 2019
2018
Genet. Program. Evolvable Mach., 2018
Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors.
Proceedings of the Genetic and Evolutionary Computation Conference, 2018
2017
Scalable genetic programming by gene-pool optimal mixing and input-space entropy-based building-block learning.
Proceedings of the Genetic and Evolutionary Computation Conference, 2017
2015
Proceedings of the Genetic and Evolutionary Computation Conference, 2015