On the Learning of ESN Linear Readouts. - Carlos M. Alaíz; José R. Dorronsoro (CAEPIA, 2011)

Sparse Linear Wind Farm Energy Forecast. - Carlos M. Alaíz; Alberto Torres; José R. Dorronsoro (ICANN (2), 2012)

Diffusion Maps and Local Models for Wind Power Prediction. - Ángela Fernández Pascual; Carlos M. Alaíz; Ana Ma González Marcos; Julia Díaz García; José R. Dorronsoro (ICANN (2), 2012)

Sparse methods for wind energy prediction. - Carlos M. Alaíz; Álvaro Barbero Jiménez; José R. Dorronsoro (IJCNN, 2012)

Group Fused Lasso. - Carlos M. Alaíz; Álvaro Barbero Jiménez; José R. Dorronsoro (ICANN, 2013)

Diffusion Methods for Wind Power Ramp Detection. - Ángela Fernández 001; Carlos M. Alaíz; Ana M. González; Julia Díaz García; José R. Dorronsoro (IWANN (1), 2013)

Kernel K-Means Low Rank Approximation for Spectral Clustering and Diffusion Maps. - Carlos M. Alaíz; Ángela Fernández 001; Yvonne Gala; José R. Dorronsoro (IDEAL, 2014)

Diffusion Maps parameters selection based on neighbourhood preservation. - Carlos M. Alaíz; Ángela Fernández 001; José R. Dorronsoro (ESANN, 2015)

Solving constrained Lasso and Elastic Net using nu-SVMs. - Carlos M. Alaíz; Alberto Torres; José R. Dorronsoro (ESANN, 2015)

The Generalized Group Lasso. - Carlos M. Alaíz; José R. Dorronsoro (IJCNN, 2015)

Convex Formulation for Kernel PCA and its Use in Semi-Supervised Learning. - Carlos M. Alaíz; Michaël Fanuel; Johan A. K. Suykens (CoRR, 2016)

Magnetic eigenmaps for community detection in directed networks. - Michaël Fanuel; Carlos M. Alaíz; Johan A. K. Suykens (CoRR, 2016)

Magnetic Eigenmaps for Visualization of Directed Networks. - Michaël Fanuel; Ángela Fernández 001; Carlos M. Alaíz; Johan A. K. Suykens (CoRR, 2016)

Revisiting FISTA for Lasso: Acceleration Strategies Over The Regularization Path. - Alejandro Catalina; Carlos M. Alaíz; José R. Dorronsoro (ESANN, 2018)

Accelerated Block Coordinate Descent for Sparse Group Lasso. - Alejandro Catalina; Carlos M. Alaíz; José R. Dorronsoro (IJCNN, 2018)

Fused Lasso Dimensionality Reduction of Highly Correlated NWP Features. - Alejandro Catalina; Carlos M. Alaíz; José R. Dorronsoro (DARE@PKDD/ECML, 2018)

Modified Frank-Wolfe algorithm for enhanced sparsity in support vector machine classifiers. - Carlos M. Alaíz; Johan A. K. Suykens (Neurocomputing, 2018)

ν-SVM solutions of constrained Lasso and Elastic net. - Alberto Torres-Barrán; Carlos M. Alaíz; José R. Dorronsoro (Neurocomputing, 2018)

Convex Formulation for Kernel PCA and Its Use in Semisupervised Learning. - Carlos M. Alaíz; Michaël Fanuel; Johan A. K. Suykens (IEEE Trans. Neural Networks Learn. Syst., 2018)

A Convex Formulation of SVM-Based Multi-task Learning. - Carlos Ruiz; Carlos M. Alaíz; José R. Dorronsoro (HAIS, 2019)

Flexible Kernel Selection in Multitask Support Vector Regression. - Carlos Ruiz; Carlos M. Alaíz; Alejandro Catalina; José R. Dorronsoro (IJCNN, 2019)

Robust classification of graph-based data. - Carlos M. Alaíz; Michaël Fanuel; Johan A. K. Suykens (Data Min. Knowl. Discov., 2019)

Visualization of the Feature Space of Neural Networks. - Carlos M. Alaíz; Ángela Fernández 001; José R. Dorronsoro (ESANN, 2020)

Modified Grid Searches for Hyper-Parameter Optimization. - David López; Carlos M. Alaíz; José R. Dorronsoro (HAIS, 2020)

Convex Graph Laplacian Multi-Task Learning SVM. - Carlos Ruiz; Carlos M. Alaíz; José R. Dorronsoro (ICANN (2), 2020)

Machine Learning Nowcasting of PV Energy Using Satellite Data. - Alejandro Catalina; Alberto Torres-Barrán; Carlos M. Alaíz; José R. Dorronsoro (Neural Process. Lett., 2020)

Adaptive Graph Laplacian for Convex Multi-Task Learning SVM. - Carlos Ruiz; Carlos M. Alaíz; José R. Dorronsoro (HAIS, 2021)

Convex formulation for multi-task L1-, L2-, and LS-SVMs. - Carlos Ruiz; Carlos M. Alaíz; José R. Dorronsoro (Neurocomputing, 2021)

Faster SVM training via conjugate SMO. - Alberto Torres-Barrán; Carlos M. Alaíz; José R. Dorronsoro (Pattern Recognit., 2021)

Convex Multi-Task Learning with Neural Networks. - Carlos Ruiz; Carlos M. Alaíz; José R. Dorronsoro (HAIS, 2022)

Structure Learning in Deep Multi-Task Models. - Carlos Ruiz; Carlos M. Alaíz; José R. Dorronsoro (HAIS, 2023)

Fault Detection in Induction Motors using Functional Dimensionality Reduction Methods. - María Barroso; José M. Bossio; Carlos M. Alaíz; Ángela Fernández Pascual (CoRR, 2023)

Learning Analytics Tools to Analyze Progress and Results With Moodle LMS Data. - Cristina Alonso-Fernández; Jose L. Jorro-Aragoneses; Carlos M. Alaíz; Pilar Rodríguez 001 (EDUCON, 2024)

Adaptive graph Laplacian MTL L1, L2 and LS-SVMs. - Carlos Ruiz; Carlos M. Alaíz; José R. Dorronsoro (Log. J. IGPL, 2024)

A survey on kernel-based multi-task learning. - Carlos Ruiz; Carlos M. Alaíz; José R. Dorronsoro (Neurocomputing, 2024)

Functional diffusion maps. - María Barroso; Carlos M. Alaíz; José L. Torrecilla; Ángela Fernández 001 (Stat. Comput., 2024)

Deep Diffusion Maps. - Sergio García-Heredia; Ángela Fernández 001; Carlos M. Alaíz (CoRR, 2025)

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers. - Miguel N. Font; Jose L. Jorro-Aragoneses; Carlos M. Alaíz (CoRR, 2025)