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:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Explaining deep learning models for ozone pollution prediction via embedded feature selection.
Appl. Soft Comput., 2024

Evolutionary Feature Selection for Time-Series Forecasting.
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

PHILNet: A novel efficient approach for time series forecasting using deep learning.
Inf. Sci., 2023

Explaining Learned Patterns in Deep Learning by Association Rules Mining.
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

Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals.
Proceedings of the Advances in Computational Intelligence, 2023

Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning.
Proceedings of the Advances in Computational Intelligence, 2023

A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia.
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

Explainable machine learning for sleep apnea prediction.
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
External clustering validity index based on chi-squared statistical test.
Inf. Sci., 2019

Analysis of the Evolution of the Spanish Labour Market Through Unsupervised Learning.
IEEE Access, 2019

2018
An approach to validity indices for clustering techniques in Big Data.
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

Applications of Computational Intelligence in Time Series.
Comput. Intell. Neurosci., 2017

2016
Improving a multi-objective evolutionary algorithm to discover quantitative association rules.
Knowl. Inf. Syst., 2016

Obtaining optimal quality measures for quantitative association rules.
Neurocomputing, 2016

A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

Discovery of Genes Implied in Cancer by Genetic Algorithms and Association Rules.
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

An Approach to Silhouette and Dunn Clustering Indices Applied to Big Data in Spark.
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

Selecting the best measures to discover quantitative association rules.
Neurocomputing, 2014

2013
ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules.
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

On the use of algorithms to discover motifs in DNA sequences.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

Inferring gene-gene associations from Quantitative Association Rules.
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

Analysis of Measures of Quantitative Association Rules.
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
Quantitative Association Rules Applied to Climatological Time Series Forecasting.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2009


  Loading...