Publications

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 (2025). Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling. Neurocomputing.

PDF Cite Code DOI arXiv URL

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.

PDF Cite Code DOI URL Code Ocean

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.

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.

PDF Cite Code DOI URL

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.

PDF Cite Code DOI URL ArXiv preprint

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.

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.

PDF Cite DOI URL

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.

PDF Cite DOI URL

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.

PDF Cite DOI URL

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.

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.

PDF Cite Code DOI URL

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.

PDF Cite DOI URL

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.

Cite Code DOI URL