Recurrent and Feedforward Polynomial Modeling of Coupled Time Series. - Vicente López 002; Ramón Huerta; José R. Dorronsoro (Neural Comput., 1993)

Analysis and Forecasting of Time Series by Averaged Scalar Products of Flow Vectors. - Carlos Santa Cruz; Ramón Huerta; José R. Dorronsoro; Vicente López 002 (Complex Syst., 1994)

Fast Automatic Architecture Selection on RBF Networks. - Ana M. González; Carlos Santa Cruz; Vicente López 002; José R. Dorronsoro (IWANN, 1995)

Neural networks in large scale bank effect recognition. - Alejandro Sierra; Carlos Santa Cruz; V. López; G. Fractman; José R. Dorronsoro; C. Aguirre; J. M. Soto; A. Medina; R. López; S. A. Keon (SNN Symposium on Neural Networks, 1995)

A Nonlinear Discriminant Algorithm for Data Projection and Feature Extraction. - Carlos Santa Cruz; José R. Dorronsoro (ICANN, 1996)

Noise Discrimination and Autoassociative Neural Networks. - Carlos Santa Cruz; José R. Dorronsoro; Juan A. Sigüenza; Vicente López 002 (IWANN, 1997)

Redes neuronales y clasificacion de datos: diagnóstico médico, reconocimiento de caracteres y detección de fraude. - José R. Dorronsoro; Vicente López 002; Carlos Santa Cruz; Juan A. Sigüenza (Inteligencia Artif., 1997)

Neural fraud detection in credit card operations. - José R. Dorronsoro; Francisco Ginel; Carmen Sanchez; Carlos Santa Cruz (IEEE Trans. Neural Networks, 1997)

A nonlinear discriminant algorithm for feature extraction and data classification. - Carlos Santa Cruz; José R. Dorronsoro (IEEE Trans. Neural Networks, 1998)

Small Sample Discrimination and Professional Performance Assessment. - David Aguado; José R. Dorronsoro; Beatriz Lucía; Carlos Santa Cruz (IWANN (2), 1999)

Architecture Selection in NLDA Networks. - José R. Dorronsoro; Ana M. González; Carlos Santa Cruz (ICANN, 2001)

Natural Gradient Learning in NLDA Networks. - José R. Dorronsoro; Ana M. González; Carlos Santa Cruz (IWANN (1), 2001)

Natural Gradient and Multiclass NLDA Networks. - José R. Dorronsoro; Ana M. González (ICANN, 2002)

Statistics of natural images using hash fractal image compression. - Kostadin Koroutchev; José R. Dorronsoro (CompSysTech, 2003)

Hash-Like Fractal Image Compression with Linear Execution Time. - Kostadin Koroutchev; José R. Dorronsoro (IbPRIA, 2003)

Linear Unit Relevance in Multiclass NLDA Networks. - José R. Dorronsoro; Ana M. González; Eduardo Serrano (IWANN (1), 2003)

A New Information Measure for Natural Images. - Kostadin Koroutchev; José R. Dorronsoro (IWANN (2), 2003)

Autoassociative neural networks and noise filtering. - José R. Dorronsoro; Vicente López 002; Carlos Santa Cruz; Juan A. Sigüenza (IEEE Trans. Signal Process., 2003)

Factorization of Natural 4×4 Patch Distributions. - Kostadin Koroutchev; José R. Dorronsoro (ECCV Workshop SMVP, 2004)

Statistical Structure of Natural 4 × 4 Image Patches. - Kostadin Koroutchev; José R. Dorronsoro (SSPR/SPR, 2004)

Parallel Perceptrons, Activation Margins and Imbalanced Training Set Pruning. - Iván Cantador; José R. Dorronsoro (IbPRIA (2), 2005)

Discriminant Parallel Perceptrons. - Ana M. González; Iván Cantador; José R. Dorronsoro (ICANN (2), 2005)

Balanced Boosting with Parallel Perceptrons. - Iván Cantador; José R. Dorronsoro (IWANN, 2005)

Boosting Parallel Perceptrons for Label Noise Reduction in Classification Problems. - Iván Cantador; José R. Dorronsoro (IWINAC (2), 2005)

Convex Perceptrons. - Daniel García; Ana M. González; José R. Dorronsoro (IDEAL, 2006)

A Note on Conjugate Natural Gradient Training of Multilayer Perceptrons. - Ana M. González; José R. Dorronsoro (IJCNN, 2006)

Accelerating Kernel Perceptron Learning. - Daniel García; Ana M. González; José R. Dorronsoro (ICANN (1), 2007)

Square Penalty Support Vector Regression. - Álvaro Barbero Jiménez; Jorge López Lázaro; José R. Dorronsoro (IDEAL, 2007)

Coefficient Structure of Kernel Perceptrons and Support Vector Reduction. - Daniel García; Ana M. González; José R. Dorronsoro (IWINAC (1), 2007)

Natural learning in NLDA networks. - Ana M. González; José R. Dorronsoro (Neural Networks, 2007)

An accelerated MDM algorithm for SVM training. - Álvaro Barbero Jiménez; Jorge López Lázaro; José R. Dorronsoro (ESANN, 2008)

Simple Clipping Algorithms for Reduced Convex Hull SVM Training. - Jorge López Lázaro; Álvaro Barbero Jiménez; José R. Dorronsoro (HAIS, 2008)

A 4-Vector MDM Algorithm for Support Vector Training. - Álvaro Barbero Jiménez; Jorge López Lázaro; José R. Dorronsoro (ICANN (1), 2008)

On the Equivalence of the SMO and MDM Algorithms for SVM Training. - Jorge López Lázaro; Álvaro Barbero Jiménez; José R. Dorronsoro (ECML/PKDD (1), 2008)

Natural conjugate gradient training of multilayer perceptrons. - Ana M. González; José R. Dorronsoro (Neurocomputing, 2008)

Finding Optimal Model Parameters by Discrete Grid Search. - Álvaro Barbero Jiménez; Jorge López Lázaro; José R. Dorronsoro (Innovations in Hybrid Intelligent Systems, 2008)

Rosen's projection method for SVM training. - Jorge López Lázaro; José R. Dorronsoro (ESANN, 2009)

A Simple Proof of the Convergence of the SMO Algorithm for Linearly Separable Problems. - Jorge López Lázaro; José R. Dorronsoro (ICANN (1), 2009)

A Simple Maximum Gain Algorithm for Support Vector Regression. - Álvaro Barbero Jiménez; José R. Dorronsoro (IWANN (1), 2009)

Cycle-breaking acceleration of SVM training. - Álvaro Barbero Jiménez; Jorge López Lázaro; José R. Dorronsoro (Neurocomputing, 2009)

Finding optimal model parameters by deterministic and annealed focused grid search. - Álvaro Barbero Jiménez; Jorge López Lázaro; José R. Dorronsoro (Neurocomputing, 2009)

Machine Learning Techniques for the Automated Classification of Adhesin-Like Proteins in the Human Protozoan Parasite Trypanosoma cruzi. - Ana M. González; Francisco Azuaje; Jose L. Ramirez; Jose F. da Silveira; José R. Dorronsoro (IEEE ACM Trans. Comput. Biol. Bioinform., 2009)

Least 1-Norm SVMs: a new SVM variant between standard and LS-SVMs. - Jorge López Lázaro; José R. Dorronsoro (ESANN, 2010)

Faster Directions for Second Order SMO. - Álvaro Barbero Jiménez; José R. Dorronsoro (ICANN (2), 2010)

A Common Framework for the Convergence of the GSK, MDM and SMO Algorithms. - Jorge López Lázaro; José R. Dorronsoro (ICANN (2), 2010)

An MDM solver for the nearest point problem in Scaled Convex Hulls. - Jorge López Lázaro; Álvaro Barbero Jiménez; José R. Dorronsoro (IJCNN, 2010)

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

Sparse LS-SVMs with L0 - norm minimization. - Jorge López Lázaro; Kris De Brabanter; José R. Dorronsoro; Johan A. K. Suykens (ESANN, 2011)

Momentum Acceleration of Least-Squares Support Vector Machines. - Jorge López Lázaro; Álvaro Barbero Jiménez; José R. Dorronsoro (ICANN (2), 2011)

Momentum Sequential Minimal Optimization: An accelerated method for Support Vector Machine training. - Álvaro Barbero Jiménez; José R. Dorronsoro (IJCNN, 2011)

Convergence of algorithms for solving the Nearest Point Problem in Reduced Convex Hulls. - Jorge López Lázaro; José R. Dorronsoro (IJCNN, 2011)

Cycle-breaking acceleration for support vector regression. - Álvaro Barbero Jiménez; José R. Dorronsoro (Neurocomputing, 2011)

Clipping algorithms for solving the nearest point problem over reduced convex hulls. - Jorge López Lázaro; Álvaro Barbero Jiménez; José R. Dorronsoro (Pattern Recognit., 2011)

Diffusion Maps for the Description of Meteorological Data. - Ángela Fernández 001; Ana M. González; Julia Díaz García; José R. Dorronsoro (HAIS (1), 2012)

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)

The convergence rate of the MDM algorithm. - Jorge López Lázaro; José R. Dorronsoro (IJCNN, 2012)

Simple Proof of Convergence of the SMO Algorithm for Different SVM Variants. - Jorge López Lázaro; José R. Dorronsoro (IEEE Trans. Neural Networks Learn. Syst., 2012)

Support Vector Forecasting of Solar Radiation Values. - Yvonne Gala; Ángela Fernández 001; Julia Díaz García; José R. Dorronsoro (HAIS, 2013)

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

The convergence rate of linearly separable SMO. - Jorge López Lázaro; José R. Dorronsoro (IJCNN, 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)

Auto-adaptative Laplacian Pyramids for high-dimensional data analysis. - Ángela Fernández 001; Neta Rabin; José R. Dorronsoro (CoRR, 2013)

Sparse one hidden layer MLPs. - Alberto Torres; David Díaz; José R. Dorronsoro (ESANN, 2014)

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)

Machine Learning Prediction of Large Area Photovoltaic Energy Production. - Ángela Fernández 001; Yvonne Gala; José R. Dorronsoro (DARE, 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)

Random Forests and Gradient Boosting for Wind Energy Prediction. - Álvaro Alonso; Alberto Torres; José R. Dorronsoro (HAIS, 2015)

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

Deep Neural Networks for Wind Energy Prediction. - David Díaz; Alberto Torres; José R. Dorronsoro (IWANN (1), 2015)

SVRs and Uncertainty Estimates in Wind Energy Prediction. - Jesús Prada; José Ramón Dorronsoro (IWANN (2), 2015)

Diffusion Maps for dimensionality reduction and visualization of meteorological data. - Ángela Fernández 001; Ana M. González; Julia Díaz García; José R. Dorronsoro (Neurocomputing, 2015)

Linear convergence rate for the MDM algorithm for the Nearest Point Problem. - Jorge López Lázaro; José R. Dorronsoro (Pattern Recognit., 2015)

Auto-adaptive Laplacian Pyramids. - Ángela Fernández 001; Neta Rabin; Dalia Fishelov; José R. Dorronsoro (ESANN, 2016)

Nesterov Acceleration for the SMO Algorithm. - Alberto Torres-Barrán; José R. Dorronsoro (ICANN (2), 2016)

Conjugate descent for the SMO algorithm. - Alberto Torres-Barrán; José R. Dorronsoro (IJCNN, 2016)

Machine Learning Prediction of Photovoltaic Energy from Satellite Sources. - Alejandro Catalina; Alberto Torres-Barrán; José R. Dorronsoro (DARE@PKDD/ECML, 2016)

Hybrid machine learning forecasting of solar radiation values. - Yvonne Gala; Ángela Fernández 001; Julia Díaz García; José R. Dorronsoro (Neurocomputing, 2016)

Satellite Based Nowcasting of PV Energy over Peninsular Spain. - Alejandro Catalina; Alberto Torres-Barrán; José R. Dorronsoro (IWANN (1), 2017)

Deep Fisher Discriminant Analysis. - David Díaz-Vico; Adil Omari; Alberto Torres-Barrán; José Ramón Dorronsoro (IWANN (2), 2017)

General Noise SVRs and Uncertainty Intervals. - Jesús Prada; José Ramón Dorronsoro (IWANN (2), 2017)

NWP Ensembles for Wind Energy Uncertainty Estimates. - Alejandro Catalina; José R. Dorronsoro (DARE@PKDD/ECML, 2017)

Deep Neural Networks for Wind and Solar Energy Prediction. - David Díaz-Vico; Alberto Torres-Barrán; Adil Omari; José R. Dorronsoro (Neural Process. Lett., 2017)

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

Gaussian Process Kernels for Support Vector Regression in Wind Energy Prediction. - Víctor de la Pompa; Alejandro Catalina; José R. Dorronsoro (IDEAL (2), 2018)

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

Deep MLPs for Imbalanced Classification. - David Díaz-Vico; Aníbal R. Figueiras-Vidal; 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)

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

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

Deep Diffusion Autoencoders. - Sara Dorado; Ángela Fernández 001; José R. Dorronsoro (IJCNN, 2019)

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

Deep Support Vector Classification and Regression. - David Díaz-Vico; Jesús Prada; Adil Omari; José R. Dorronsoro (IWINAC (2), 2019)

Day-Ahead Price Forecasting for the Spanish Electricity Market. - Álvaro Romero; José Ramón Dorronsoro; Julia Díaz García (Int. J. Interact. Multim. Artif. Intell., 2019)

Regression tree ensembles for wind energy and solar radiation prediction. - Alberto Torres-Barrán; Álvaro Alonso; José R. Dorronsoro (Neurocomputing, 2019)

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

Supervised Hyperparameter Estimation for Anomaly Detection. - Juan Bella; Ángela Fernández 001; José R. Dorronsoro (HAIS, 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)

Auto-adaptive multi-scale Laplacian Pyramids for modeling non-uniform data. - Ángela Fernández 001; Neta Rabin; Dalia Fishelov; José R. Dorronsoro (Eng. Appl. Artif. Intell., 2020)

Deep support vector neural networks. - David Díaz-Vico; Jesús Prada; Adil Omari; José R. Dorronsoro (Integr. Comput. Aided Eng., 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)

Deep Least Squares Fisher Discriminant Analysis. - David Díaz-Vico; José R. Dorronsoro (IEEE Trans. Neural Networks Learn. Syst., 2020)

Companion Losses for Deep Neural Networks. - David Díaz-Vico; Ángela Fernández 001; José R. Dorronsoro (HAIS, 2021)

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)

Companion Losses for Ordinal Regression. - David Díaz-Vico; Ángela Fernández 001; José R. Dorronsoro (HAIS, 2022)

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

Supervised outlier detection for classification and regression. - Ángela Fernández 001; Juan Bella; José R. Dorronsoro (Neurocomputing, 2022)

Robust Losses in Deep Regression. - Adrián Rubio; José R. Dorronsoro (HAIS, 2023)

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

Companion Classification Losses for Regression Problems. - Aitor Sánchez-Ferrera; José R. Dorronsoro (HAIS, 2023)

Nyström and RFF Ensembles for Large-Scale Kernel Predictions. - Blanca Cano; Ángela Fernández Pascual; José R. Dorronsoro (HAIS (1), 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)