María Martínez-Ballesteros

51 papers B 1C 3Misc 10Journal 25Unranked 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
A novel interpretable ozone forecasting approach based on deep learning with masked residual connections.
Environ. Model. Softw.
Pablo Reina-Jiménez, M. J. Jiménez-Navarro, Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, María Martínez-Ballesteros
2026 J jnl
Tree-based vs. deep learning in time series: A prescriptive framework for performance-driven model selection.
Appl. Soft Comput.
Pablo Reina-Jiménez, María Martínez-Ballesteros, José C. Riquelme
2025 J jnl
A New Metric Based on Association Rules to Assess Feature-Attribution Explainability Techniques for Time Series Forecasting.
IEEE Trans. Pattern Anal. Mach. Intell.
Angela del Robledo Troncoso-García, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso
2025 J jnl
A novel approach based on clustering and optimized ensemble deep learning for energy consumption forecasting in Ethiopia.
Neurocomputing
E. Tefera Habtemariam, María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez
2025 Misc conf
Bioinspired evolutionary metaheuristic based on COVID spread for discovering numerical association rules.
SAC
Cristina Herruzo-Lodeiro, Francesc Rodríguez-Díaz, Alicia Troncoso, María Martínez-Ballesteros
2025 — conf
Comparison of Explainable Machine Learning Methods for Early Prediction of Student Performance in Programming Courses.
AIED Companion (2)
Ziwei Wang, Irena Koprinska, María Martínez-Ballesteros, Alicia Troncoso, Bryn Jeffries
2025 — conf
Deep Learning or Trees? A Trade-off Analysis for Multivariate Time Series Forecasting.
IWANN (1)
Pablo Reina-Jiménez, María Martínez-Ballesteros, José C. Riquelme
2025 J jnl
Embedded feature selection for neural networks via learnable drop layer.
Log. J. IGPL
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Isabel Sofia Brito, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2025 — conf
Feature Importance in Association Rule-Based Explanations for Time Series Forecasting.
IDEAL (2)
A. R. Troncoso-García, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora
2024 Misc conf
Evolutionary Feature Selection for Time-Series Forecasting.
SAC
Maria Lourdes Linares-Barrera, Manuel Jesús Jiménez-Navarro, Isabel Sofia Brito, José C. Riquelme, María Martínez-Ballesteros
2024 J jnl
Explaining deep learning models for ozone pollution prediction via embedded feature selection.
Appl. Soft Comput.
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2024 J jnl
From simple to complex: a sequential method for enhancing time series forecasting with deep learning.
Log. J. IGPL
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso, Gualberto Asencio-Cortés
2024 — conf
Multi-Objective Lagged Feature Selection Based on Dependence Coefficient for Time-Series Forecasting.
CAEPIA
Maria Lourdes Linares-Barrera, Manuel Jesús Jiménez-Navarro, José C. Riquelme, María Martínez-Ballesteros
2024 — conf
Time Series Forecasting in Agriculture: Explainable Deep Learning with Lagged Feature Selection.
SOCO (1)
A. R. Troncoso-García, M. J. Jiménez-Navarro, Maria Lourdes Linares-Barrera, Isabel Sofia Brito, Francisco Martínez-Álvarez, María Martínez-Ballesteros
2023 Misc conf
A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma.
HAIS
Maria Lourdes Linares-Barrera, María Martínez-Ballesteros, José Manuel García-Heredia, José C. Riquelme
2023 Misc conf
A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia.
HAIS
E. Tefera, María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez
2023 Misc conf
A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal.
SAC
Manuel Jesús Jiménez-Navarro, María Martínez-Ballesteros, Isabel Sofia Brito, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2023 J jnl
A new approach based on association rules to add explainability to time series forecasting models.
Inf. Fusion
A. R. Troncoso-García, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso
2023 J jnl
A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting.
J. Big Data
Manuel Jesús Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2023 — conf
Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation.
CISIS-ICEUTE
Manuel Jesús Jiménez-Navarro, Belén Vega-Márquez, José María Luna-Romera, Manuel Carranza-García, María Martínez-Ballesteros
2023 — conf
Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals.
IWANN (1)
A. R. Troncoso-García, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora
2023 — conf
Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning.
IWANN (2)
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2023 Misc conf
Evolutionary computation to explain deep learning models for time series forecasting.
SAC
Angela Troncoso-García, Alicia Troncoso Lora, Francisco Martínez-Álvarez, María Martínez-Ballesteros
2023 — conf
Explaining Learned Patterns in Deep Learning by Association Rules Mining.
SOCO (2)
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2023 J jnl
PHILNet: A novel efficient approach for time series forecasting using deep learning.
Inf. Sci.
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2022 Misc conf
A novel approach to discover numerical association based on the coronavirus optimization algorithm.
SAC
C. Segarra-Martín, María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez
2022 B conf
Explainable machine learning for sleep apnea prediction.
KES
A. R. Troncoso-García, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso
2022 — conf
Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection.
SOCO
Manuel Jesús Jiménez-Navarro, María Martínez-Ballesteros, Isabel Sofia Sousa Brito, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2020 J jnl
Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance.
Artif. Intell. Medicine
Laura Macías-García, María Martínez-Ballesteros, José María Luna-Romera, José Manuel García-Heredia, Jorge García-Gutiérrez, José Cristóbal Riquelme Santos
2019 J jnl
Analysis of the Evolution of the Spanish Labour Market Through Unsupervised Learning.
IEEE Access
José María Luna-Romera, Fernando Núñez-Hernández, María Martínez-Ballesteros, José C. Riquelme, Carlos Usabiaga
2019 J jnl
External clustering validity index based on chi-squared statistical test.
Inf. Sci.
José María Luna-Romera, María Martínez-Ballesteros, Jorge García-Gutiérrez, José C. Riquelme
2018 J jnl
An approach to validity indices for clustering techniques in Big Data.
Prog. Artif. Intell.
José María Luna-Romera, Jorge García-Gutiérrez, María Martínez-Ballesteros, José Cristóbal Riquelme Santos
2018 J jnl
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems.
Knowl. Based Syst.
Diana Martín, María Martínez-Ballesteros, Diego García-Gil, Jesús Alcalá-Fdez, Francisco Herrera, José Cristóbal Riquelme Santos
2017 J jnl
A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation.
J. Biomed. Informatics
Laura Macías-García, José María Luna-Romera, Jorge García-Gutiérrez, María Martínez-Ballesteros, José Cristóbal Riquelme Santos, Ricardo González-Cámpora
2017 J jnl
Applications of Computational Intelligence in Time Series.
Comput. Intell. Neurosci.
Francisco Martínez-Álvarez, Alicia Troncoso, Jorge Reyes, María Martínez-Ballesteros, José C. Riquelme
2017 J jnl
Machine learning techniques to discover genes with potential prognosis role in Alzheimer's disease using different biological sources.
Inf. Fusion
María Martínez-Ballesteros, José Manuel García-Heredia, Isabel A. Nepomuceno-Chamorro, José Cristóbal Riquelme Santos
2016 Misc conf
A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting.
HAIS
Ricardo L. Talavera-Llames, Rubén Pérez-Chacón, María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez
2016 Misc conf
Discovery of Genes Implied in Cancer by Genetic Algorithms and Association Rules.
HAIS
Alejandro Sánchez Medina, Alberto Gil Pichardo, José Manuel García-Heredia, María Martínez-Ballesteros
2016 J jnl
Improving a multi-objective evolutionary algorithm to discover quantitative association rules.
Knowl. Inf. Syst.
María Martínez-Ballesteros, Alicia Troncoso Lora, Francisco Martínez-Álvarez, José C. Riquelme
2016 J jnl
Obtaining optimal quality measures for quantitative association rules.
Neurocomputing
María Martínez-Ballesteros, Alicia Troncoso, Francisco Martínez-Álvarez, José C. Riquelme
2015 J jnl
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets.
Integr. Comput. Aided Eng.
María Martínez-Ballesteros, Jaume Bacardit, Alicia Troncoso Lora, José C. Riquelme
2014 J jnl
Discovering gene association networks by multi-objective evolutionary quantitative association rules.
J. Comput. Syst. Sci.
María Martínez-Ballesteros, Isabel A. Nepomuceno-Chamorro, José C. Riquelme
2014 J jnl
Selecting the best measures to discover quantitative association rules.
Neurocomputing
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2013 Misc conf
ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules.
HAIS
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2011 J jnl
An evolutionary algorithm to discover quantitative association rules in multidimensional time series.
Soft Comput.
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme
2011 — conf
Analysis of Measures of Quantitative Association Rules.
HAIS (2)
María Martínez-Ballesteros, José Cristóbal Riquelme Santos
2011 C conf
Inferring gene-gene associations from Quantitative Association Rules.
ISDA
María Martínez-Ballesteros, Isabel A. Nepomuceno-Chamorro, José C. Riquelme
2011 — conf
Mining Quantitative Association Rules in Microarray Data using Evolutive Algorithms.
ICAART (1)
María Martínez-Ballesteros, Cristina Rubio-Escudero, José C. Riquelme, Francisco Martínez-Álvarez
2011 C conf
On the use of algorithms to discover motifs in DNA sequences.
ISDA
Cristina Rubio-Escudero, Francisco Martínez-Álvarez, María Martínez-Ballesteros, José C. Riquelme
2010 J jnl
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution.
Integr. Comput. Aided Eng.
María Martínez-Ballesteros, Alicia Troncoso Lora, Francisco Martínez-Álvarez, José C. Riquelme
2009 C conf
Quantitative Association Rules Applied to Climatological Time Series Forecasting.
IDEAL
María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme