José R. Dorronsoro

发表

Natural conjugate gradient training of multilayer perceptrons

Ana M. González, José R. Dorronsoro, Ana M. González, 2006, Neurocomputing.

Machine Learning Nowcasting of PV Energy Using Satellite Data

José R. Dorronsoro, Alejandro Catalina, Alberto Torres-Barrán, 2019, Neural Processing Letters.

A Nonlinear Discriminant Algorithm for Data Projection and Feature Extraction

José R. Dorronsoro, Carlos Santa Cruz, 1996, ICANN.

Simple Proof of Convergence of the SMO Algorithm for Different SVM Variants

José R. Dorronsoro, Jorge López Lázaro, J. R. Dorronsoro, 2012, IEEE Transactions on Neural Networks and Learning Systems.

Square Penalty Support Vector Regression

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2007, IDEAL.

The convergence rate of linearly separable SMO

José R. Dorronsoro, Jorge López Lázaro, J. Lázaro, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Cycle-breaking acceleration for support vector regression

José R. Dorronsoro, Álvaro Barbero Jiménez, Á. Jiménez, 2011, Neurocomputing.

Satellite Based Nowcasting of PV Energy over Peninsular Spain

José R. Dorronsoro, Alejandro Catalina, Alberto Torres-Barrán, 2017, IWANN.

Regression tree ensembles for wind energy and solar radiation prediction

Álvaro Alonso, José R. Dorronsoro, Alberto Torres-Barrán, 2017, Neurocomputing.

Knowledge-Based Systems for Real-Time Process Control: The Mip Project

José R. Dorronsoro, Xavier Alamán, Carlos Aguirre, 1992 .

Sparse Linear Wind Farm Energy Forecast

José R. Dorronsoro, Carlos M. Alaíz, Alberto Torres, 2012, ICANN.

Flexible Kernel Selection in Multitask Support Vector Regression

José R. Dorronsoro, Alejandro Catalina, Carlos M. Alaíz, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Stochastic Specificity in Neural Interaction

José R. Dorronsoro, Vicente López, Juan A. Sigüenza, 1993 .

Hash-Like Fractal Image Compression with Linear Execution Time

Kostadin Koroutchev, José R. Dorronsoro, 2003, IbPRIA.

Natural Gradient Learning in NLDA Networks

José R. Dorronsoro, Carlos Santa Cruz, Ana M. González, 2001, IWANN.

Cycle-breaking acceleration of SVM training

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2009, Neurocomputing.

Deep Diffusion Autoencoders

José R. Dorronsoro, Sara Dorado, Ángela Fernández, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Auto-adaptative Laplacian Pyramids for high-dimensional data analysis pdf

José R. Dorronsoro, Ángela Fernández, Neta Rabin, 2013, ArXiv.

Extreme Sample Classification and Credit Card Fraud Detection

José R. Dorronsoro, Carlos Santa Cruz, Ana M. González, 2002 .

Linear Unit Relevance in Multiclass NLDA Networks

Eduardo Serrano, José R. Dorronsoro, Ana M. González, 2003, IWANN.

Sparse one hidden layer MLPs

José R. Dorronsoro, David Díaz, Alberto Torres, 2014, ESANN.

An accelerated MDM algorithm for SVM training

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2008, ESANN.

A New Information Measure for Natural Images

Kostadin Koroutchev, José R. Dorronsoro, 2003, IWANN.

Convex Graph Laplacian Multi-Task Learning SVM

José R. Dorronsoro, Carlos M. Alaíz, Carlos Ruiz, 2020, ICANN.

Accelerated Block Coordinate Descent for Sparse Group Lasso

José R. Dorronsoro, Alejandro Catalina, Carlos M. Alaíz, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Auto-adaptive Laplacian Pyramids

José R. Dorronsoro, Ángela Fernández, Neta Rabin, 2016, ESANN.

Momentum Acceleration of Least-Squares Support Vector Machines

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2011, ICANN.

Sparse LS-SVMs with L0 - norm minimization

Johan A. K. Suykens, José R. Dorronsoro, Kris De Brabanter, 2011, ESANN.

Deep Neural Networks for Wind Energy Prediction

José R. Dorronsoro, David Díaz, Alberto Torres, 2015, IWANN.

Simple Clipping Algorithms for Reduced Convex Hull SVM Training

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2008, HAIS.

Noise Discrimination and Autoassociative Neural Networks

José R. Dorronsoro, Carlos Santa Cruz, Juan A. Sigüenza, 1997, IWANN.

Multitask Support Vector Regression for Solar and Wind Energy Prediction

José R. Dorronsoro, Carlos M. Alaíz, Carlos Ruiz, 2020, Energies.

Convex Perceptrons

José R. Dorronsoro, Ana M. González, Daniel García, 2006, IDEAL.

Modified Grid Searches for Hyper-Parameter Optimization

José R. Dorronsoro, Carlos M. Alaíz, David López, 2020, HAIS.

Machine Learning Techniques for the Automated Classification of Adhesin-Like Proteins in the Human Protozoan Parasite Trypanosoma cruzi

Francisco Azuaje, José R. Dorronsoro, Ana M. González, 2009, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Deep Support Vector Classification and Regression

José R. Dorronsoro, Adil Omari, David Díaz-Vico, 2019, IWINAC.

An MDM solver for the nearest point problem in Scaled Convex Hulls

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Balanced Boosting with Parallel Perceptrons

José R. Dorronsoro, Iván Cantador, Iván Cantador, 2005, IWANN.

Deep MLPs for Imbalanced Classification

Aníbal R. Figueiras-Vidal, José R. Dorronsoro, David Díaz-Vico, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Artificial neural networks - ICANN 2002 : international conference, Madrid, Spain, August 28-30, 2002 : proceedings

José R. Dorronsoro, 2002 .

Faster Directions for Second Order SMO

José R. Dorronsoro, Álvaro Barbero Jiménez, J. R. Dorronsoro, 2010, ICANN.

Coefficient Structure of Kernel Perceptrons and Support Vector Reduction

José R. Dorronsoro, Ana M. González, Daniel García, 2007, IWINAC.

Machine Learning Prediction of Photovoltaic Energy from Satellite Sources

José R. Dorronsoro, Alejandro Catalina, Alberto Torres-Barrán, 2016, DARE@PKDD/ECML.

KNOWLEDGE-BASED SYSTEMS FOR REAL-TIME PROCESS CONTROL: THE MIP PROJECT

José R. Dorronsoro, Xavier Alamán, Carlos Aguirre, 1993 .

Fast Automatic Architecture Selection on RBF Networks

José R. Dorronsoro, Carlos Santa Cruz, Vicente López, 1995, IWANN.

A Simple Proof of the Convergence of the SMO Algorithm for Linearly Separable Problems

José R. Dorronsoro, Jorge López Lázaro, 2009, ICANN.

AUTOASSOCIATIVE NEURAL NETWORKS AND TIME SERIES FILTERING

José R. Dorronsoro, Carlos Santa Cruz, Vicente López, 2001 .

On the Learning of ESN Linear Readouts

José R. Dorronsoro, Carlos M. Alaíz, 2011, CAEPIA.

ν-SVM solutions of constrained Lasso and Elastic net

José R. Dorronsoro, Alberto Torres-Barrán, Carlos M. Alaíz, 2018, Neurocomputing.

Supervised Hyperparameter Estimation for Anomaly Detection

José R. Dorronsoro, Ángela Fernández, Juan Bella, 2020, HAIS.

Rosen's projection method for SVM training

José R. Dorronsoro, Jorge López Lázaro, 2009, ESANN.

Natural learning in NLDA networks

José R. Dorronsoro, Ana M. González, 2007, Neural Networks.

Deep Fisher Discriminant Analysis

José R. Dorronsoro, Alberto Torres-Barrán, Adil Omari, 2017, IWANN.

Convergence of algorithms for solving the Nearest Point Problem in Reduced Convex Hulls

José R. Dorronsoro, Jorge López Lázaro, 2011, The 2011 International Joint Conference on Neural Networks.

Machine Learning Prediction of Global Photovoltaic Energy in Spain

José R. Dorronsoro, Yvonne Gala, Ángela Fernández, 2014 .

A Note on Conjugate Natural Gradient Training of Multilayer Perceptrons

José R. Dorronsoro, Ana M. González, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Architecture Selection in NLDA Networks

José R. Dorronsoro, Carlos Santa Cruz, Ana M. González, 2001, ICANN.

Factorization of Natural 4×4 Patch Distributions

Kostadin Koroutchev, José R. Dorronsoro, K. Koroutchev, 2004, ECCV Workshop SMVP.

The Generalized Group Lasso

José R. Dorronsoro, Carlos M. Alaíz, J. R. Dorronsoro, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

A Convex Formulation of SVM-Based Multi-task Learning

José R. Dorronsoro, Carlos M. Alaíz, Carlos Ruiz, 2019, HAIS.

A Common Framework for the Convergence of the GSK, MDM and SMO Algorithms

José R. Dorronsoro, Jorge López Lázaro, 2010, ICANN.

Machine Learning Prediction of Large Area Photovoltaic Energy Production

José R. Dorronsoro, Ángela Fernández, Yvonne Gala, 2014, DARE.

Accelerating Kernel Perceptron Learning

José R. Dorronsoro, Ana M. González, Daniel García, 2007, ICANN.

Autoassociative neural networks and noise filtering

José R. Dorronsoro, Carlos Santa Cruz, Juan A. Sigüenza, 2003, IEEE Trans. Signal Process..

Deep Neural Networks for Wind and Solar Energy Prediction

José R. Dorronsoro, Alberto Torres-Barrán, Adil Omari, 2017, Neural Processing Letters.

Revisiting FISTA for Lasso: Acceleration Strategies Over The Regularization Path

José R. Dorronsoro, Alejandro Catalina, Carlos M. Alaíz, 2018, ESANN.

Diffusion Maps for dimensionality reduction and visualization of meteorological data

José R. Dorronsoro, Ana M. González, Ángela Fernández, 2015, Neurocomputing.

Finding optimal model parameters by deterministic and annealed focused grid search

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2009, Neurocomputing.

Conjugate descent for the SMO algorithm

José R. Dorronsoro, Alberto Torres-Barrán, J. R. Dorronsoro, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Proceedings of the International Conference on Artificial Neural Networks

José R. Dorronsoro, J. R. Dorronsoro, 2002 .

Random Forests and Gradient Boosting for Wind Energy Prediction

Álvaro Alonso, José R. Dorronsoro, Alberto Torres, 2015, HAIS.

Small Sample Discrimination and Professional Performance Assessment

José R. Dorronsoro, Carlos Santa Cruz, David Aguado, 1999, IWANN.

Statistical Structure of Natural 4 × 4 Image Patches

Kostadin Koroutchev, José R. Dorronsoro, K. Koroutchev, 2004, SSPR/SPR.

Diffusion Maps parameters selection based on neighbourhood preservation

José R. Dorronsoro, Carlos M. Alaíz, Ángela Fernández, 2015, ESANN.

On the Equivalence of the SMO and MDM Algorithms for SVM Training

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2008, ECML/PKDD.

Auto-adaptive multi-scale Laplacian Pyramids for modeling non-uniform data

José R. Dorronsoro, Neta Rabin, Dalia Fishelov, 2020, Eng. Appl. Artif. Intell..

Momentum Sequential Minimal Optimization: An accelerated method for Support Vector Machine training

José R. Dorronsoro, Álvaro Barbero Jiménez, J. R. Dorronsoro, 2011, The 2011 International Joint Conference on Neural Networks.

Redes neuronales y clasificacion de datos: diagnóstico médico, reconocimiento de caracteres y detección de fraude

José R. Dorronsoro, Carlos Santa Cruz, Juan A. Sigüenza, 1997, Inteligencia Artif..

Sparse methods for wind energy prediction

José R. Dorronsoro, Carlos M. Alaíz, Álvaro Barbero Jiménez, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Automatic neural generalized font identification

José R. Dorronsoro, Analía González, C. Santa Cruz, 1998 .

Kernel K-Means Low Rank Approximation for Spectral Clustering and Diffusion Maps

José R. Dorronsoro, Carlos M. Alaíz, Ángela Fernández, 2014, IDEAL.

High wind and energy specific models for global production forecast

José R. Dorronsoro, Álvaro Barbero Jiménez, Carlos María Alaíz Gudín, 2009 .

Finding Optimal Model Parameters by Discrete Grid Search

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2008, Innovations in Hybrid Intelligent Systems.

Least 1-Norm SVMs: a new SVM variant between standard and LS-SVMs

José R. Dorronsoro, Jorge López Lázaro, 2010, ESANN.

Diffusion Maps and Local Models for Wind Power Prediction

José R. Dorronsoro, Carlos M. Alaíz, Julia Díaz García, 2012, ICANN.

A 4-Vector MDM Algorithm for Support Vector Training

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2008, ICANN.

Solving constrained Lasso and Elastic Net using nu-SVMs

José R. Dorronsoro, Carlos M. Alaíz, Alberto Torres, 2015, ESANN.

SVRs and Uncertainty Estimates in Wind Energy Prediction

José R. Dorronsoro, Jesús Prada, J. R. Dorronsoro, 2015, IWANN.

Parallel Perceptrons, Activation Margins and Imbalanced Training Set Pruning

José R. Dorronsoro, Iván Cantador, 2005, IbPRIA.

Visualization of the Feature Space of Neural Networks

José R. Dorronsoro, Carlos M. Alaíz, Ángela Fernández, 2020, ESANN.

Recurrent and Feedforward Polynomial Modeling of Coupled Time Series

José R. Dorronsoro, Ramón Huerta, Vicente López, 1993, Neural Computation.

Gaussian Process Kernels for Support Vector Regression in Wind Energy Prediction

José R. Dorronsoro, Alejandro Catalina, Víctor de la Pompa, 2018, IDEAL.

Hybrid machine learning forecasting of solar radiation values

José R. Dorronsoro, Ángela Fernández, Yvonne Gala, 2016, Neurocomputing.

Boosting Parallel Perceptrons for Label Noise Reduction in Classification Problems

José R. Dorronsoro, Iván Cantador, 2005, IWINAC.

AUTOMATIC CLASSIFICATION OF VISUAL EVOKED POTENTIALS BY FEEDFORWARD NEURAL NETWORKS

José R. Dorronsoro, Vicente López, Juan A. Sigüenza, 1991 .

Nesterov Acceleration for the SMO Algorithm

José R. Dorronsoro, Alberto Torres-Barrán, J. R. Dorronsoro, 2016, ICANN.

The convergence rate of the MDM algorithm

José R. Dorronsoro, Jorge López Lázaro, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Neural networks in large scale bank effect recognition

José R. Dorronsoro, C. Santa Cruz, Rafael Lopez, 1995, SNN Symposium on Neural Networks.

Diffusion Maps for the Description of Meteorological Data

José R. Dorronsoro, Ana M. González, Ángela Fernández, 2012, HAIS.

Deep support vector neural networks

José R. Dorronsoro, Adil Omari, David Díaz-Vico, 2020, Integr. Comput. Aided Eng..

Support Vector Forecasting of Solar Radiation Values

José R. Dorronsoro, Ángela Fernández, Yvonne Gala, 2013, HAIS.

General Noise SVRs and Uncertainty Intervals

José R. Dorronsoro, Jesús Prada, J. Prada, 2017, IWANN.

Neural fraud detection in credit card operations

José R. Dorronsoro, Carlos Santa Cruz, Francisco Ginel, 1997, IEEE Trans. Neural Networks.

Analysis and Forecasting of Time Series by Averaged Scalar Products of Flow Vectors

José R. Dorronsoro, Carlos Santa Cruz, Ramón Huerta, 1994, Complex Syst..

Linear convergence rate for the MDM algorithm for the Nearest Point Problem

José R. Dorronsoro, Jorge López Lázaro, 2015, Pattern Recognit..

Discriminant Parallel Perceptrons

José R. Dorronsoro, Iván Cantador, Ana M. González, 2005, ICANN.

Diffusion Methods for Wind Power Ramp Detection

José R. Dorronsoro, Carlos M. Alaíz, Ana M. González, 2013, IWANN.

Natural Gradient and Multiclass NLDA Networks

José R. Dorronsoro, Ana M. González, 2002, ICANN.

Natural conjugate gradient training of multilayer perceptrons

José R. Dorronsoro, Ana M. González, J. R. Dorronsoro, 2006, Neurocomputing.

A Simple Maximum Gain Algorithm for Support Vector Regression

José R. Dorronsoro, Álvaro Barbero Jiménez, 2009, IWANN.

Formal integrators and neural networks

José R. Dorronsoro, Vicente López, 1990 .

Day-Ahead Price Forecasting for the Spanish Electricity Market

José R. Dorronsoro, Julia Díaz García, Álvaro Romero, 2019, Int. J. Interact. Multim. Artif. Intell..

Group Fused Lasso

José R. Dorronsoro, Carlos M. Alaíz, Álvaro Barbero Jiménez, 2013, ICANN.

Clipping algorithms for solving the nearest point problem over reduced convex hulls

José R. Dorronsoro, Jorge López Lázaro, Álvaro Barbero Jiménez, 2011, Pattern Recognit..

Large scale neural form recognition

José R. Dorronsoro, C. Santa Cruz, G. Practman, 1998 .

Fused Lasso Dimensionality Reduction of Highly Correlated NWP Features

José R. Dorronsoro, Alejandro Catalina, Carlos M. Alaíz, 2018, DARE@PKDD/ECML.

A nonlinear discriminant algorithm for feature extraction and data classification

José R. Dorronsoro, Carlos Santa Cruz, 1998, IEEE Trans. Neural Networks.

Parallel Perceptrons and Training Set Selection for Imbalanced Classification Problems

José R. Dorronsoro, Iván Cantador, 2004 .

Convex formulation for multi-task L1-, L2-, and LS-SVMs

José R. Dorronsoro, Carlos M. Alaíz, Carlos Ruiz, 2021, Neurocomputing.

Adaptive Graph Laplacian for Convex Multi-Task Learning SVM

José R. Dorronsoro, Carlos M. Alaíz, Carlos Ruiz, 2021, HAIS.

Companion Losses for Deep Neural Networks

José R. Dorronsoro, David Díaz-Vico, Angela Fernández, 2021, HAIS.

Local State-Space Reconstruction Using Averaged Scalar Products of the Dynamical-System Flow Vectors

José R. Dorronsoro, C. Santa Cruz, Ramon Huerta, 1995 .

Kernel Methods for Wide Area Wind Power Forecasting

José R. Dorronsoro, Jorge López, Álvaro Barbero, 2008 .

General noise support vector regression with non-constant uncertainty intervals for solar radiation prediction

José R. Dorronsoro, J. PRADA, J. R. DORRONSORO, 2018 .

NWP Ensembles for Wind Energy Uncertainty Estimates

José R. Dorronsoro, J. R. Dorronsoro, Alejandro Catalina, 2017, DARE@PKDD/ECML.

Weighted Hardy Spaces on Siegel's Half Planes

José R. Dorronsoro, J. R. Dorronsoro, 1986 .

Mean Oscillation and Besov Spaces

José R. Dorronsoro, J. R. Dorronsoro, 1985, Canadian Mathematical Bulletin.

Factorization and structure of natural 4×4 patch densities

José R. Dorronsoro, J. R. Dorronsoro, K. Koroutchev, 2006 .

Advances in Computational Intelligence: 19th Mexican International Conference on Artificial Intelligence, MICAI 2020, Mexico City, Mexico, October 12–17, 2020, Proceedings, Part II

Ahmed Abbou, José R. Dorronsoro, Mohammed Akherraz, 2020, Lecture Notes in Computer Science.

Implicit Wiener series analysis of epileptic seizure recordings

Moritz Grosse-Wentrup, José R. Dorronsoro, Bernhard Scholkopf, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Faster SVM Training via Conjugate SMO pdf

José R. Dorronsoro, Carlos M. Alaíz, Alberto Torres-Barr'an, 2020, Pattern Recognit..

A survey on kernel-based multi-task learning

José R. Dorronsoro, Carlos M. Alaíz, Carlos Ruiz, 2024, Neurocomputing.