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ORCIDJosé R. Dorronsoro
José Ramón Dorronsoro
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2020 – today
- 2024
[j29]Carlos Ruiz
, Carlos M. Alaíz, José R. Dorronsoro:
A survey on kernel-based multi-task learning. Neurocomputing 577: 127255 (2024)- [c87]Blanca Cano, Ángela Fernández Pascual, José R. Dorronsoro:
Nyström and RFF Ensembles for Large-Scale Kernel Predictions. HAIS (1) 2024: 165-176 - 2023
- [c86]Aitor Sánchez-Ferrera, José R. Dorronsoro:
Companion Classification Losses for Regression Problems. HAIS 2023: 219-230 - [c85]Adrián Rubio, José R. Dorronsoro:
Robust Losses in Deep Regression. HAIS 2023: 256-268 - [c84]Carlos Ruiz, Carlos M. Alaíz, José R. Dorronsoro:
Structure Learning in Deep Multi-Task Models. HAIS 2023: 269-280 - 2022
- [j28]Ángela Fernández, Juan Bella, José R. Dorronsoro:
Supervised outlier detection for classification and regression. Neurocomputing 486: 77-92 (2022) - [c83]David Díaz-Vico, Ángela Fernández, José R. Dorronsoro:
Companion Losses for Ordinal Regression. HAIS 2022: 211-222 - [c82]Carlos Ruiz, Carlos M. Alaíz, José R. Dorronsoro:
Convex Multi-Task Learning with Neural Networks. HAIS 2022: 223-235 - 2021
- [j27]Carlos Ruiz, Carlos M. Alaíz, José R. Dorronsoro:
Convex formulation for multi-task L1-, L2-, and LS-SVMs. Neurocomputing 456: 599-608 (2021) - [j26]Alberto Torres-Barrán, Carlos M. Alaíz, José R. Dorronsoro:
Faster SVM training via conjugate SMO. Pattern Recognit. 111: 107644 (2021) - [c81]Carlos Ruiz, Carlos M. Alaíz, José R. Dorronsoro:
Adaptive Graph Laplacian for Convex Multi-Task Learning SVM. HAIS 2021: 219-230 - [c80]David Díaz-Vico, Ángela Fernández, José R. Dorronsoro:
Companion Losses for Deep Neural Networks. HAIS 2021: 538-549 - 2020
- [j25]Ángela Fernández, Neta Rabin, Dalia Fishelov, José R. Dorronsoro:
Auto-adaptive multi-scale Laplacian Pyramids for modeling non-uniform data. Eng. Appl. Artif. Intell. 93: 103682 (2020) - [j24]David Díaz-Vico, Jesús Prada, Adil Omari, José R. Dorronsoro:
Deep support vector neural networks. Integr. Comput. Aided Eng. 27(4): 389-402 (2020) - [j23]Alejandro Catalina, Alberto Torres-Barrán, Carlos M. Alaíz, José R. Dorronsoro:
Machine Learning Nowcasting of PV Energy Using Satellite Data. Neural Process. Lett. 52(1): 97-115 (2020) - [j22]David Díaz-Vico, José R. Dorronsoro:
Deep Least Squares Fisher Discriminant Analysis. IEEE Trans. Neural Networks Learn. Syst. 31(8): 2752-2763 (2020) - [c79]Carlos M. Alaíz, Ángela Fernández, José R. Dorronsoro:
Visualization of the Feature Space of Neural Networks. ESANN 2020: 169-174 - [c78]David López, Carlos M. Alaíz, José R. Dorronsoro:
Modified Grid Searches for Hyper-Parameter Optimization. HAIS 2020: 221-232 - [c77]Juan Bella, Ángela Fernández, José R. Dorronsoro:
Supervised Hyperparameter Estimation for Anomaly Detection. HAIS 2020: 233-244 - [c76]Carlos Ruiz, Carlos M. Alaíz, José R. Dorronsoro:
Convex Graph Laplacian Multi-Task Learning SVM. ICANN (2) 2020: 142-154 - [i2]Alberto Torres-Barrán, Carlos M. Alaíz, José R. Dorronsoro:
Faster SVM Training via Conjugate SMO. CoRR abs/2003.08719 (2020)
2010 – 2019
- 2019
- [j21]Álvaro Romero, José Ramón Dorronsoro, Julia Díaz García:
Day-Ahead Price Forecasting for the Spanish Electricity Market. Int. J. Interact. Multim. Artif. Intell. 5(4): 42-50 (2019) - [j20]Alberto Torres-Barrán, Álvaro Alonso, José R. Dorronsoro:
Regression tree ensembles for wind energy and solar radiation prediction. Neurocomputing 326-327: 151-160 (2019) - [c75]Carlos Ruiz, Carlos M. Alaíz, José R. Dorronsoro:
A Convex Formulation of SVM-Based Multi-task Learning. HAIS 2019: 404-415 - [c74]Sara Dorado, Ángela Fernández, José R. Dorronsoro:
Deep Diffusion Autoencoders. IJCNN 2019: 1-8 - [c73]Carlos Ruiz, Carlos M. Alaíz, Alejandro Catalina, José R. Dorronsoro:
Flexible Kernel Selection in Multitask Support Vector Regression. IJCNN 2019: 1-8 - [c72]David Díaz-Vico, Jesús Prada, Adil Omari, José R. Dorronsoro:
Deep Support Vector Classification and Regression. IWINAC (2) 2019: 33-43 - 2018
- [j19]Alberto Torres-Barrán, Carlos M. Alaíz, José R. Dorronsoro:
ν-SVM solutions of constrained Lasso and Elastic net. Neurocomputing 275: 1921-1931 (2018) - [c71]Alejandro Catalina, Carlos M. Alaíz, José R. Dorronsoro:
Revisiting FISTA for Lasso: Acceleration Strategies Over The Regularization Path. ESANN 2018 - [c70]Víctor de la Pompa, Alejandro Catalina, José R. Dorronsoro:
Gaussian Process Kernels for Support Vector Regression in Wind Energy Prediction. IDEAL (2) 2018: 147-154 - [c69]Alejandro Catalina, Carlos M. Alaíz, José R. Dorronsoro:
Accelerated Block Coordinate Descent for Sparse Group Lasso. IJCNN 2018: 1-8 - [c68]David Díaz-Vico, Aníbal R. Figueiras-Vidal, José R. Dorronsoro:
Deep MLPs for Imbalanced Classification. IJCNN 2018: 1-7 - [c67]Alejandro Catalina, Carlos M. Alaíz, José R. Dorronsoro:
Fused Lasso Dimensionality Reduction of Highly Correlated NWP Features. DARE@PKDD/ECML 2018: 13-26 - 2017
- [j18]David Díaz-Vico, Alberto Torres-Barrán, Adil Omari, José R. Dorronsoro:
Deep Neural Networks for Wind and Solar Energy Prediction. Neural Process. Lett. 46(3): 829-844 (2017) - [c66]David Díaz-Vico, Adil Omari, Alberto Torres-Barrán, José Ramón Dorronsoro:
Deep Fisher Discriminant Analysis. IWANN (2) 2017: 501-512 - [c65]Alejandro Catalina, Alberto Torres-Barrán, José R. Dorronsoro:
Satellite Based Nowcasting of PV Energy over Peninsular Spain. IWANN (1) 2017: 685-697 - [c64]Jesús Prada, José Ramón Dorronsoro:
General Noise SVRs and Uncertainty Intervals. IWANN (2) 2017: 734-746 - [c63]Alejandro Catalina, José R. Dorronsoro:
NWP Ensembles for Wind Energy Uncertainty Estimates. DARE@PKDD/ECML 2017: 121-132 - 2016
- [j17]Yvonne Gala, Ángela Fernández, Julia Díaz García, José R. Dorronsoro:
Hybrid machine learning forecasting of solar radiation values. Neurocomputing 176: 48-59 (2016) - [c62]Ángela Fernández, Neta Rabin, Dalia Fishelov, José R. Dorronsoro:
Auto-adaptive Laplacian Pyramids. ESANN 2016 - [c61]Alberto Torres-Barrán, José R. Dorronsoro:
Nesterov Acceleration for the SMO Algorithm. ICANN (2) 2016: 243-250 - [c60]Alberto Torres-Barrán, José R. Dorronsoro:
Conjugate descent for the SMO algorithm. IJCNN 2016: 3817-3824 - [c59]Alejandro Catalina, Alberto Torres-Barrán, José R. Dorronsoro:
Machine Learning Prediction of Photovoltaic Energy from Satellite Sources. DARE@PKDD/ECML 2016: 31-42 - 2015
- [j16]Ángela Fernández, Ana M. González, Julia Díaz García, José R. Dorronsoro:
Diffusion Maps for dimensionality reduction and visualization of meteorological data. Neurocomputing 163: 25-37 (2015) - [j15]Jorge López Lázaro, José R. Dorronsoro:
Linear convergence rate for the MDM algorithm for the Nearest Point Problem. Pattern Recognit. 48(4): 1510-1522 (2015) - [c58]Carlos M. Alaíz, Ángela Fernández, José R. Dorronsoro:
Diffusion Maps parameters selection based on neighbourhood preservation. ESANN 2015 - [c57]Carlos M. Alaíz, Alberto Torres, José R. Dorronsoro:
Solving constrained Lasso and Elastic Net using nu-SVMs. ESANN 2015 - [c56]Álvaro Alonso, Alberto Torres, José R. Dorronsoro:
Random Forests and Gradient Boosting for Wind Energy Prediction. HAIS 2015: 26-37 - [c55]Carlos M. Alaíz, José R. Dorronsoro:
The Generalized Group Lasso. IJCNN 2015: 1-8 - [c54]David Díaz, Alberto Torres, José R. Dorronsoro:
Deep Neural Networks for Wind Energy Prediction. IWANN (1) 2015: 430-443 - [c53]Jesús Prada, José Ramón Dorronsoro:
SVRs and Uncertainty Estimates in Wind Energy Prediction. IWANN (2) 2015: 564-577 - 2014
- [c52]Alberto Torres, David Díaz, José R. Dorronsoro:
Sparse one hidden layer MLPs. ESANN 2014 - [c51]Carlos M. Alaíz, Ángela Fernández, Yvonne Gala, José R. Dorronsoro:
Kernel K-Means Low Rank Approximation for Spectral Clustering and Diffusion Maps. IDEAL 2014: 239-246 - [c50]Ángela Fernández, Yvonne Gala, José R. Dorronsoro:
Machine Learning Prediction of Large Area Photovoltaic Energy Production. DARE 2014: 38-53 - 2013
- [c49]Yvonne Gala, Ángela Fernández, Julia Díaz García, José R. Dorronsoro:
Support Vector Forecasting of Solar Radiation Values. HAIS 2013: 51-60 - [c48]Carlos M. Alaíz, Álvaro Barbero Jiménez, José R. Dorronsoro:
Group Fused Lasso. ICANN 2013: 66-73 - [c47]Jorge López Lázaro, José R. Dorronsoro:
The convergence rate of linearly separable SMO. IJCNN 2013: 1-7 - [c46]Ángela Fernández, Carlos M. Alaíz, Ana M. González, Julia Díaz García, José R. Dorronsoro:
Diffusion Methods for Wind Power Ramp Detection. IWANN (1) 2013: 106-113 - [i1]Ángela Fernández, Neta Rabin, José R. Dorronsoro:
Auto-adaptative Laplacian Pyramids for high-dimensional data analysis. CoRR abs/1311.6594 (2013) - 2012
- [j14]Jorge López Lázaro, José R. Dorronsoro:
Simple Proof of Convergence of the SMO Algorithm for Different SVM Variants. IEEE Trans. Neural Networks Learn. Syst. 23(7): 1142-1147 (2012) - [c45]Ángela Fernández, Ana M. González, Julia Díaz García, José R. Dorronsoro:
Diffusion Maps for the Description of Meteorological Data. HAIS (1) 2012: 276-287 - [c44]Carlos M. Alaíz, Alberto Torres, José R. Dorronsoro:
Sparse Linear Wind Farm Energy Forecast. ICANN (2) 2012: 557-564 - [c43]Ángela Fernández Pascual, Carlos M. Alaíz, Ana Ma González Marcos, Julia Díaz García, José R. Dorronsoro:
Diffusion Maps and Local Models for Wind Power Prediction. ICANN (2) 2012: 565-572 - [c42]Carlos M. Alaíz, Álvaro Barbero Jiménez, José R. Dorronsoro:
Sparse methods for wind energy prediction. IJCNN 2012: 1-7 - [c41]Jorge López Lázaro, José R. Dorronsoro:
The convergence rate of the MDM algorithm. IJCNN 2012: 1-7 - 2011
- [j13]Álvaro Barbero Jiménez, José R. Dorronsoro:
Cycle-breaking acceleration for support vector regression. Neurocomputing 74(16): 2649-2656 (2011) - [j12]Jorge López Lázaro, Álvaro Barbero Jiménez, José R. Dorronsoro:
Clipping algorithms for solving the nearest point problem over reduced convex hulls. Pattern Recognit. 44(3): 607-614 (2011) - [c40]Carlos M. Alaíz, José R. Dorronsoro:
On the Learning of ESN Linear Readouts. CAEPIA 2011: 124-133 - [c39]Jorge López Lázaro, Kris De Brabanter, José R. Dorronsoro, Johan A. K. Suykens:
Sparse LS-SVMs with L0 - norm minimization. ESANN 2011 - [c38]Jorge López Lázaro, Álvaro Barbero Jiménez, José R. Dorronsoro:
Momentum Acceleration of Least-Squares Support Vector Machines. ICANN (2) 2011: 135-142 - [c37]Álvaro Barbero Jiménez, José R. Dorronsoro:
Momentum Sequential Minimal Optimization: An accelerated method for Support Vector Machine training. IJCNN 2011: 370-377 - [c36]Jorge López Lázaro, José R. Dorronsoro:
Convergence of algorithms for solving the Nearest Point Problem in Reduced Convex Hulls. IJCNN 2011: 413-420 - 2010
- [c35]Jorge López Lázaro, José R. Dorronsoro:
Least 1-Norm SVMs: a new SVM variant between standard and LS-SVMs. ESANN 2010 - [c34]Álvaro Barbero Jiménez, José R. Dorronsoro:
Faster Directions for Second Order SMO. ICANN (2) 2010: 30-39 - [c33]Jorge López Lázaro, José R. Dorronsoro:
A Common Framework for the Convergence of the GSK, MDM and SMO Algorithms. ICANN (2) 2010: 82-87 - [c32]Jorge López Lázaro, Álvaro Barbero Jiménez, José R. Dorronsoro:
An MDM solver for the nearest point problem in Scaled Convex Hulls. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [j11]Álvaro Barbero Jiménez, Jorge López Lázaro, José R. Dorronsoro:
Cycle-breaking acceleration of SVM training. Neurocomputing 72(7-9): 1398-1406 (2009) - [j10]Álvaro Barbero Jiménez, Jorge López Lázaro, José R. Dorronsoro:
Finding optimal model parameters by deterministic and annealed focused grid search. Neurocomputing 72(13-15): 2824-2832 (2009) - [j9]Ana M. González, Francisco Azuaje, Jose L. Ramirez, Jose F. da Silveira, José R. Dorronsoro:
Machine Learning Techniques for the Automated Classification of Adhesin-Like Proteins in the Human Protozoan Parasite Trypanosoma cruzi. IEEE ACM Trans. Comput. Biol. Bioinform. 6(4): 695-702 (2009) - [c31]Jorge López Lázaro, José R. Dorronsoro:
Rosen's projection method for SVM training. ESANN 2009 - [c30]Jorge López Lázaro, José R. Dorronsoro:
A Simple Proof of the Convergence of the SMO Algorithm for Linearly Separable Problems. ICANN (1) 2009: 904-912 - [c29]Álvaro Barbero Jiménez, José R. Dorronsoro:
A Simple Maximum Gain Algorithm for Support Vector Regression. IWANN (1) 2009: 73-80 - 2008
- [j8]Ana M. González, José R. Dorronsoro:
Natural conjugate gradient training of multilayer perceptrons. Neurocomputing 71(13-15): 2499-2506 (2008) - [c28]Álvaro Barbero Jiménez, Jorge López Lázaro, José R. Dorronsoro:
An accelerated MDM algorithm for SVM training. ESANN 2008: 421-426 - [c27]Jorge López Lázaro, Álvaro Barbero Jiménez, José R. Dorronsoro:
Simple Clipping Algorithms for Reduced Convex Hull SVM Training. HAIS 2008: 369-377 - [c26]Álvaro Barbero Jiménez, Jorge López Lázaro, José R. Dorronsoro:
A 4-Vector MDM Algorithm for Support Vector Training. ICANN (1) 2008: 315-324 - [c25]Jorge López Lázaro, Álvaro Barbero Jiménez, José R. Dorronsoro:
On the Equivalence of the SMO and MDM Algorithms for SVM Training. ECML/PKDD (1) 2008: 288-300 - [p1]Álvaro Barbero Jiménez, Jorge López Lázaro, José R. Dorronsoro:
Finding Optimal Model Parameters by Discrete Grid Search. Innovations in Hybrid Intelligent Systems 2008: 120-127 - 2007
- [j7]Ana M. González, José R. Dorronsoro:
Natural learning in NLDA networks. Neural Networks 20(5): 610-620 (2007) - [c24]Daniel García, Ana M. González, José R. Dorronsoro:
Accelerating Kernel Perceptron Learning. ICANN (1) 2007: 159-168 - [c23]Álvaro Barbero Jiménez, Jorge López Lázaro, José R. Dorronsoro:
Square Penalty Support Vector Regression. IDEAL 2007: 537-546 - [c22]Daniel García, Ana M. González, José R. Dorronsoro:
Coefficient Structure of Kernel Perceptrons and Support Vector Reduction. IWINAC (1) 2007: 337-345 - 2006
- [c21]Ana M. González, José R. Dorronsoro:
Natural Conjugate Gradient Training of Multilayer Perceptrons. ICANN (1) 2006: 169-177 - [c20]Daniel García, Ana M. González, José R. Dorronsoro:
Convex Perceptrons. IDEAL 2006: 578-585 - [c19]Ana M. González, José R. Dorronsoro:
A Note on Conjugate Natural Gradient Training of Multilayer Perceptrons. IJCNN 2006: 887-891 - 2005
- [c18]Iván Cantador, José R. Dorronsoro:
Parallel Perceptrons, Activation Margins and Imbalanced Training Set Pruning. IbPRIA (2) 2005: 43-50 - [c17]Ana M. González, Iván Cantador, José R. Dorronsoro:
Discriminant Parallel Perceptrons. ICANN (2) 2005: 13-18 - [c16]Iván Cantador, José R. Dorronsoro:
Balanced Boosting with Parallel Perceptrons. IWANN 2005: 208-216 - [c15]Iván Cantador, José R. Dorronsoro:
Boosting Parallel Perceptrons for Label Noise Reduction in Classification Problems. IWINAC (2) 2005: 586-593 - 2004
- [c14]Kostadin Koroutchev, José R. Dorronsoro:
Factorization of Natural 4×4 Patch Distributions. ECCV Workshop SMVP 2004: 165-174 - [c13]Kostadin Koroutchev, José R. Dorronsoro:
Statistical Structure of Natural 4 × 4 Image Patches. SSPR/SPR 2004: 452-460 - 2003
- [j6]José R. Dorronsoro, Vicente López, Carlos Santa Cruz, Juan A. Sigüenza:
Autoassociative neural networks and noise filtering. IEEE Trans. Signal Process. 51(5): 1431-1438 (2003) - [c12]Kostadin Koroutchev, José R. Dorronsoro:
Statistics of natural images using hash fractal image compression. CompSysTech 2003: 242-249 - [c11]Kostadin Koroutchev, José R. Dorronsoro:
Hash-Like Fractal Image Compression with Linear Execution Time. IbPRIA 2003: 395-402 - [c10]José R. Dorronsoro, Ana M. González, Eduardo Serrano:
Linear Unit Relevance in Multiclass NLDA Networks. IWANN (1) 2003: 174-181 - [c9]Kostadin Koroutchev, José R. Dorronsoro:
A New Information Measure for Natural Images. IWANN (2) 2003: 520-527 - 2002
- [c8]José R. Dorronsoro, Ana M. González:
Natural Gradient and Multiclass NLDA Networks. ICANN 2002: 673-680 - [e1]José R. Dorronsoro:
Artificial Neural Networks - ICANN 2002, International Conference, Madrid, Spain, August 28-30, 2002, Proceedings. Lecture Notes in Computer Science 2415, Springer 2002, ISBN 3-540-44074-7 [contents] - 2001
- [c7]José R. Dorronsoro, Ana M. González, Carlos Santa Cruz:
Architecture Selection in NLDA Networks. ICANN 2001: 27-32 - [c6]José R. Dorronsoro, Ana M. González, Carlos Santa Cruz:
Natural Gradient Learning in NLDA Networks. IWANN (1) 2001: 427-434
1990 – 1999
- 1999
- [c5]David Aguado, José R. Dorronsoro, Beatriz Lucía, Carlos Santa Cruz:
Small Sample Discrimination and Professional Performance Assessment. IWANN (2) 1999: 558-566 - 1998
- [j5]Carlos Santa Cruz, José R. Dorronsoro:
A nonlinear discriminant algorithm for feature extraction and data classification. IEEE Trans. Neural Networks 9(6): 1370-1376 (1998) - 1997
- [j4]José R. Dorronsoro, Vicente López, Carlos Santa Cruz, Juan A. Sigüenza:
Redes neuronales y clasificacion de datos: diagnóstico médico, reconocimiento de caracteres y detección de fraude. Inteligencia Artif. 1(1): 41-47 (1997) - [j3]José R. Dorronsoro, Francisco Ginel, Carmen Sanchez, Carlos Santa Cruz:
Neural fraud detection in credit card operations. IEEE Trans. Neural Networks 8(4): 827-834 (1997) - [c4]Carlos Santa Cruz, José R. Dorronsoro, Juan A. Sigüenza, Vicente López:
Noise Discrimination and Autoassociative Neural Networks. IWANN 1997: 1213-1220 - 1996
- [c3]Carlos Santa Cruz, José R. Dorronsoro:
A Nonlinear Discriminant Algorithm for Data Projection and Feature Extraction. ICANN 1996: 563-568 - 1995
- [c2]Ana M. González, Carlos Santa Cruz, Vicente López, José R. Dorronsoro:
Fast Automatic Architecture Selection on RBF Networks. IWANN 1995: 291-297 - [c1]Alejandro Sierra, Carlos Santa Cruz, V. López, G. Fractman, José R. Dorronsoro, C. Aguirre, J. M. Soto, A. Medina, R. López, S. A. Keon:
Neural networks in large scale bank effect recognition. SNN Symposium on Neural Networks 1995: 393-396 - 1994
- [j2]Carlos Santa Cruz, Ramón Huerta, José R. Dorronsoro, Vicente López:
Analysis and Forecasting of Time Series by Averaged Scalar Products of Flow Vectors. Complex Syst. 8(1) (1994) - 1993
- [j1]Vicente López, Ramón Huerta, José R. Dorronsoro:
Recurrent and Feedforward Polynomial Modeling of Coupled Time Series. Neural Comput. 5(5): 795-811 (1993)
Coauthor Index
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