María Martínez-Ballesteros
Orcid: 0000-0003-3160-7414
According to our database1,
María Martínez-Ballesteros
authored at least 42 papers
between 2009 and 2024.
Collaborative distances:
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Bibliography
2024
Explaining deep learning models for ozone pollution prediction via embedded feature selection.
Appl. Soft Comput., 2024
Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024
Multi-Objective Lagged Feature Selection Based on Dependence Coefficient for Time-Series Forecasting.
Proceedings of the Advances in Artificial Intelligence, 2024
2023
A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting.
J. Big Data, December, 2023
A new approach based on association rules to add explainability to time series forecasting models.
Inf. Fusion, June, 2023
Inf. Sci., 2023
Proceedings of the 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023), 2023
Evolutionary computation to explain deep learning models for time series forecasting.
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023
A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal.
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023
Proceedings of the Advances in Computational Intelligence, 2023
Proceedings of the Advances in Computational Intelligence, 2023
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023
A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma.
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023
Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation.
Proceedings of the International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023), 2023
2022
Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection.
Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022
A novel approach to discover numerical association based on the coronavirus optimization algorithm.
Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022
Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 26th International Conference KES-2022, 2022
2021
Spanish adaptation and validation of the User Version of the Mobile Application Rating Scale (uMARS).
J. Am. Medical Informatics Assoc., 2021
2020
Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance.
Artif. Intell. Medicine, 2020
2019
Inf. Sci., 2019
Analysis of the Evolution of the Spanish Labour Market Through Unsupervised Learning.
IEEE Access, 2019
2018
Prog. Artif. Intell., 2018
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems.
Knowl. Based Syst., 2018
2017
A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation.
J. Biomed. Informatics, 2017
Machine learning techniques to discover genes with potential prognosis role in Alzheimer's disease using different biological sources.
Inf. Fusion, 2017
Comput. Intell. Neurosci., 2017
2016
Improving a multi-objective evolutionary algorithm to discover quantitative association rules.
Knowl. Inf. Syst., 2016
Neurocomputing, 2016
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016
Proceedings of the Advances in Artificial Intelligence, 2016
2015
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets.
Integr. Comput. Aided Eng., 2015
2014
Discovering gene association networks by multi-objective evolutionary quantitative association rules.
J. Comput. Syst. Sci., 2014
Neurocomputing, 2014
2013
Proceedings of the Hybrid Artificial Intelligent Systems - 8th International Conference, 2013
2011
An evolutionary algorithm to discover quantitative association rules in multidimensional time series.
Soft Comput., 2011
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011
Mining Quantitative Association Rules in Microarray Data using Evolutive Algorithms.
Proceedings of the ICAART 2011 - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence, Volume 1, 2011
Proceedings of the Hybrid Artificial Intelligent Systems - 6th International Conference, 2011
2010
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution.
Integr. Comput. Aided Eng., 2010
2009
Proceedings of the Intelligent Data Engineering and Automated Learning, 2009