Publications

PyKernelLogit: Penalised maximum likelihood estimation of Kernel Logistic Regression in Python
José Ángel Martín-Baos, Ricardo García-Ródenas, María Luz López-García, Luis Rodriguez-Benitez (2024). PyKernelLogit: Penalised maximum likelihood estimation of Kernel Logistic Regression in Python. Software Impacts.
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Scalable Kernel Logistic Regression with Nyström Approximation: Theoretical Analysis and Application to Discrete Choice Modelling
José Ángel Martín-Baos, Ricardo García-Ródenas, Luis Rodriguez-Benitez, Michel Bierlaire (2024). Scalable Kernel Logistic Regression with Nyström Approximation: Theoretical Analysis and Application to Discrete Choice Modelling.
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The time slot allocation problem in liberalised passenger railway markets: a multi-objective approach
Nikola Bešinović, Ricardo García-Ródenas, María Luz López-García, Julio Alberto López-Gómez, José Ángel Martín-Baos (2024). The time slot allocation problem in liberalised passenger railway markets: a multi-objective approach.
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ROBIN: Rail mOBIlity simulatioN
E. Del Castillo-Herrera, R. García-Ródenas, L. Jimenez-Linares, M. L. López-García, J. A. López-Gómez, J. A. Martín-Baos, J. Moreno-Garcia, D. Muñoz-Valero, L. Rodriguez-Benitez, E. A. Villarrubia-Martin (2024). ROBIN: Rail mOBIlity simulatioN. Transportation Research Procedia.
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A prediction and behavioural analysis of machine learning methods for modelling travel mode choice
José Ángel Martín-Baos, Julio Alberto López-Gómez, Luis Rodriguez-Benitez, Tim Hillel, Ricardo García-Ródenas (2023). A prediction and behavioural analysis of machine learning methods for modelling travel mode choice. Transportation Research Part C: Emerging Technologies.
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Machine learning methods applied to transport demand modelling
José Ángel Martín-Baos (2023). Machine learning methods applied to transport demand modelling. Universidad de Castilla-La Mancha.
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A comparative study of machine learning, deep neural networks and random utility maximization models for travel mode choice modelling
José Carlos García-García, Ricardo García-Ródenas, Julio Alberto López-Gómez, José Ángel Martín-Baos (2022). A comparative study of machine learning, deep neural networks and random utility maximization models for travel mode choice modelling. Transportation Research Procedia.
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IoT based monitoring of air quality and traffic using regression analysis
José Ángel Martín-Baos, Luis Rodriguez-Benitez, Ricardo García-Ródenas, Jun Liu (2022). IoT based monitoring of air quality and traffic using regression analysis. Applied Soft Computing.
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A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression
José Ángel Martín-Baos, Ricardo García-Ródenas, Luis Rodriguez-Benitez (2021). A Python package for performing penalized maximum likelihood estimation of conditional logit models using Kernel Logistic Regression. Transportation Research Procedia.
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Revisiting kernel logistic regression under the random utility models perspective. An interpretable machine-learning approach
José Ángel Martín-Baos, Ricardo García-Ródenas, Luis Rodriguez-Benitez (2021). Revisiting kernel logistic regression under the random utility models perspective. An interpretable machine-learning approach. Transportation Letters.
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A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs
Ricardo García-Ródenas, José Carlos García-García, Jesús López-Fidalgo, José Ángel Martín-Baos, Weng Kee Wong (2020). A comparison of general-purpose optimization algorithms for finding optimal approximate experimental designs. Computational Statistics and Data Analysis.
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Discrete choice modeling using Kernel Logistic Regression
José Ángel Martín-Baos, Ricardo García-Ródenas, María Luz López-García, Luis Rodriguez-Benitez (2020). Discrete choice modeling using Kernel Logistic Regression. Transportation Research Procedia.
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A general approach to fuzzy community detection in social networks
Alfonso Niño, Sebastián Reyes, José Ángel Martín-Baos, Camelia Muñoz-Caro (2019). A general approach to fuzzy community detection in social networks. Proceedings - International Conference on Computer Communications and Networks, ICCCN.
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