Publications
2024
Deep Learning for Multi-Output Regression using Gradient Boosting. Seyedsaman Emami, Gonzalo Martínez-Muñoz IEEE Access. [DOI]
Towards Efficient Modeling and Inference in Multi-dimensional Gaussian Process State-space Models. Zhidi Lin, Juan Maroñas, Ying Li, Feng Yin, Sergios Theodoridis Acoustics, Speech and Signal Processing - ICASSP. [DOI]
2023
Companion Classification Losses for Regression Problems. Aitor Sánchez-Ferrera, Jose R. Dorronsoro International Conference on Hybrid Artificial Intelligence Systems. [DOI]
Robust Losses in Deep Regression. Adrián Rubio, Jose R. Dorronsoro International Conference on Hybrid Artificial Intelligence Systems. [DOI]
Structure Learning in Deep Multi-Task Models. Carlos Ruiz, Carlos M. Alaíz, José R. Dorronsoro International Conference on Hybrid Artificial Intelligence Systems. [DOI]
Multiscale extensions for enhancing coarse grid computations. Neta Rabin, Ángela Fernández, Dalia Fishelov Journal of Computational and Applied Mathematics. [DOI]
Functional diffusion maps. María Barroso, Carlos M. Alaíz, José L. Torrecilla, Ángela Fernández Statistics and Computing. [DOI]
Parallel predictive entropy search for multi-objective Bayesian optimization with constraints applied to the tuning of machine learning algorithms. Eduardo C. Garrido-Merchán, Daniel Fernández-Sánchez, Daniel Hernández-Lobato Expert Systems with Applications. [DOI]
Improved max-value entropy search for multi-objective bayesian optimization with constraints. Daniel Fernández-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato Neurocomputing. [DOI]
Gaussian processes for missing value imputation. Bahram Jafrasteh, Daniel Hernández-Lobato, Simón Pedro Lubián-López, Isabel Benavente-Fernández Knowledge-Based Systems. [DOI]
Inference over radiative transfer models using variational and expectation maximization methods. Daniel Heestermans Svendsen, Daniel Hernández-Lobato, Luca Martino, Valero Laparra, Álvaro Moreno-Martínez, Gustau Camps-Valls Machine Learning. [DOI]
Deep Variational Implicit Processes. Luis A. Ortega, Simón Rodríguez Santana, Daniel Hernández-Lobato International Conference on Learning Representations. [DOI]
Gaussianization of LA-ICP_Ms features to improve calibration in forensic glass comparison. Pablo Ramírez-Hereda, Daniel Ramos, Juan Maroñas, Sergio Álvarez-Balanya, Jose Almiral Forensic Science International. [DOI]
Efficient Transformed Gaussian Processes for non-stationary dependent multiclass classification. Juan Maroñas, Daniel Hernández-Lobato International Conference on Machine Learning. [DOI]
Sequential Training of Neural Networks with Gradient Boosting, Seyedsaman Emami and Gonzalo Martínez-Muñoz IEEE Access. [DOI]
A Gradient Boosting Approach for Training Convolutional and Deep Neural Networks. Seyedsaman Emami, Gonzalo Martínez-Muñoz IEEE Open Journal of Signal Processing. [DOI]
Multi-Task Gradient Boosting. Seyedsaman Emami, Carlos Ruiz-Pastor, Gonzalo Martínez-Muñoz International Conference on Hybrid Artificial Intelligence Systems. Springer, Cham [DOI]
2022
Building heterogeneous ensembles by pooling homogeneous ensembles. Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez. International Journal of Machine Learning and Cybernetics. [DOI]
SVM Ensembles on a Budget. David Nevado, Gonzalo Martínez-Muñoz, Alberto Suárez Artificial Neural Networks and Machine Learning - ICANN. [DOI]
Multioutput Regression Neural Network Training via Gradient Boosting. Seyedsaman Emami and Gonzalo Martínez-Muñoz European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - ESANN 2022. [DOI]
Diversity and Generalizatrion in Neural Network Ensembles. Luis A. Ortega, Rafael Cabañas y Andrés R. Masegosa AISTATS 2022. [Link]
Alpha-divergence minimization for deep Gaussian processes. Carlos Villacampa-Calvo, Gonzalo Hernández-Muñoz, Daniel Hernández-Lobato International Journal of Approximate Reasoning. [DOI]
Function-space Inference with Sparse Implicit Processes. S. Rodrı́guez-Santana, B. Zaldivar, D. Hernandez-Lobato International Conference on Machine Learning. [Link]
Adversarial α-divergence minimization for Bayesian approximate inference. S. Rodrı́guez-Santana, D. Hernandez-Lobato International Conference on Machine Learning. [DOI]
Input Dependent Sparse Gaussian Processes. B. Jafrasteh, C. Villacampa-Calvo, D. Hernandez-Lobato Hybrid Artificial Intelligent Systems - HAIS 2022. [Link]
Companion Losses for Ordinal Regression. D. Díaz-Vico, A. Fernández, J. R. Dorronsoro Hybrid Artificial Intelligent Systems - HAIS 2022. [DOI]
Convex Multi-Task Learning with Neural Networks. Carlos Ruiz, Carlos M. Alaíz and José R. Dorronsoro. Hybrid Artificial Intelligent Systems - HAIS 2022. [DOI]
Improving Laplacian Pyramids Regression with Localization in Frequency and Time. B. Hen, N. Rabin, A. Fernández European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - ESANN 2022. [DOI]
Supervised Outlier Detection for Classification and Regression. A. Fernández, J. Bella, J. R. Dorronsoro Neurocomputing. [DOI]
BioMedIA: A Complete Voice-to-Voice Generative Question Answering System for the Biomedical Domain in Spanish. Alejandro Vaca Serrano, David Betancur Sanchez, Alba Segurado, Guillem Garcia Subies, Alvaro Barbero Jimenez North American Chapter of the Association for Computational Linguistics Conference: LatinX in AI (LXAI) Research Workshop 2022. [Link]
RigoBERTa: A State-of-the-Art Language Model For Spanish. Alejandro Vaca Serrano, Guillem Garcia Subies, Helena Montoro Zamorano, Nuria Aldama Garcia, Doaa Samy, David Betancur Sanchez, Antonio Moreno Sandoval, Marta Guerrero Nieto, Alvaro Barbero Jimenez arXiv e-prints . [Link]
2021
Optimal classification of Gaussian processes in homo- and heteroscedastic settings. Torrecilla, J.L., Ramos-Carreño, C., Sánchez-Montañés, M. Stat Comput 30, 1091–1111. [DOI]
scikit-fda: A Python package for Functional Data Analysis. RAMOS-CARREÑO, Carlos; TORRECILLA, José Luis; SUÁREZ, Alberto. International Workshop on Functional and Operationl Statisctics. [Link]
Objective functions from Bayesian optimization to locate additional drillholes. Bahram Jafrasteh and Alberto Suárez Computers & Geosciences. [DOI]
Adaptive Graph Laplacian for Convex Multi-Task Learning SVM. Ruiz C., Alaíz C., Dorronsoro J. International Conference on Hybrid Artificial Intelligence Systems. [DOI]
Convex Formulation for Multi-Task L1-, L2-, and LS-SVMs. Ruiz C., Alaíz C., Dorronsoro J. Neurocomputing. [DOI]
Identifies Polyps in Real Time With Accuracy 96.67% in Screening Colonoscopy Using Convolutional Neural Networks(CNN). Hadi Abooei Mehriz 2nd PhD Research Symposium in Health Sciences and Biomedicine.
Companion Losses for Deep Neural Networks. David Díaz-Vico, Ángela Fernández, José R. Dorronsoro International Conference on Hybrid Artificial Intelligence Systems. [DOI]
Super Local Models for Wind Power Detection. María Barroso, Ángela Fernández International Conference on Hybrid Artificial Intelligence Systems. [DOI]
Multitask SVR Models for Solar and Wind Energy Prediction. Ruiz C., Alaíz C., Dorronsoro J. Energies. [DOI]
Transhumanismo y Consciencia Fenoménica. Eduardo C. Garrido Merchán Congreso Razón Abierta 2021. Universidad Francisco de Vitoria.
A Similarity Measure of Gaussian Process Predictive Distributions. Asencio-Martín, L. and Garrido-Merchán, E. Lecture Notes in Artificial Intelligence (CAEPIA 2021)
A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications. Balázs, C., van Beekveld, M., Caron, S., Dillon, B. M., Farmer, B., Fowlie, A., Garrido-Merchán, Eduardo C.,..., White, M. Journal of High Energy Physics, 2021.
Multi-class Gaussian Process Classification with Noisy Inputs. Villacampa-Calvo, C., Zaldivar, B., Garrido-Merchán, E. C., Hernández-Lobato, D. Journal of Machine Learning Research.
Towards Automatic Bayesian Optimization: A first step involving acquisition functions. Jariego-Pérez, L. C. and Garrido-Merchán, E. C. Lecture Notes in Artificial Intelligence (CAEPIA 2021).
Comparing BERT against traditional machine learning text classification. González-Carvajal, S. and Garrido-Merchán, E. C. Proceedings of the XIX Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2021).
Fuzzy Stochastic Timed Petri Nets for Causal Properties Representation. Sobrino, A., Garrido-Merchán, E. C. and Puente, C. Journal of New Mathematics and Natural Computation. 2021.
Activation-level uncertainty in deep neural networks. Pablo Morales-Alvarez, Daniel Hernández-Lobato, Rafael Molina, José Miguel Hernández-Lobato ICLR. [DOI]
Importance Weighted Adversarial Variational Bayes. Marta Gómez-Sancho, Daniel Hernández-Lobato HAIS. [DOI]
Adversarial α-divergence minimization for Bayesian approximate inference. Simón Rodríguez Santana, Daniel Hernández-Lobato Neurocomputing. [DOI]
Inference over radiative transfer models using variational and expectation maximization methods. Daniel Heestermans Svendsen, Daniel Hernández-Lobato, Luca Martino, Valero Laparra, Álvaro Moreno-Martínez, Gustau Camps-Valls. Machine Learning. [DOI]
Classifying Spanish se constructions: from bag of words to language models. Nuria Aldama García, Álvaro Barbero Jiménez. Procesamiento del Lenguaje Natural,. [Article]
2020
Data-Driven Democracy? Automated Decision-Making, Difference and Preferences. Benítez, Jesus, Margarita Gómez-Reino, and Alberto Suárez APSA Preprints [DOI]
Visualization of the Feature Space of Neural Networks. Carlos M. Alaíz, Ángela Fernández, José R. Dorronsoro European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 169-174 ISBN: 978-2-87587-074-2
Supervised Hyperparameter Estimation for Anomaly Detection. Juan Bella, Ángela Fernández, José R. Dorronsoro International Conference on Hybrid Artificial Intelligence Systems, 233-244 [DOI]
Auto-adaptive multi-scale Laplacian Pyramids for modeling non-uniform data. Ángela Fernández, Neta Rabin, Dalia Fishelov, José R. Dorronsoro. Engineering Applications of Artificial Intelligence, 93, 103682 [DOI]
Deep support vector neural networks. David Díaz-Vico, Jesús Prada Alonso, Adil Omari, José R. Dorronsoro. Integrated Computer Aided Engineering, 2020. [DOI]
Alpha divergence minimization in multi-class Gaussian process classification. Villacampa-Calvo C. and Hernández-Lobato D. Neurocomputing, 2020. [DOI]
Deep gaussian processes using expectation propagation and monte carlo methods. Hernández-Muñoz G., Villacampa-Calvo C., and Hernández-Lobato D. ECML-PKDD. [DOI]
A comparative analysis of gradient boosting algorithms. Bentéjac, Candice, Csorgo, Anna, Martínez-Muñoz, Gonzalo. Artificial Intelligence Review, (in press). [DOI]
A machine learning model to assess the ecosystem response to water policy measures in the Tagus River Basin (Spain). Carlotta Valerio, Lucia De Stefano, Gonzalo Martínez-Muñoz, Alberto Garrido. Science of The Total Environment, 750, 2021 [DOI]
Identifying cheating users in online courses. Sangalli, V.A., Martínez-Muñoz, G., Canabate, E.P. IEEE Global Engineering Education Conference, EDUCON, 2020, pp. 1168-1175. [DOI]
Uncertainty Weighted Causal Graphs. Eduardo C. Garrido-Merchán, Cristina Puente, Alejandro Sobrino, Jose Angel Olivas. International Conference on Hybrid Artificial Intelligence Systems, (HAIS). 2020.
Fake News Detection by means of Uncertainty Weighted Causal Graphs. Eduardo C. Garrido-Merchán, Cristina Puente, Rafael Palacios. International Conference on Hybrid Artificial Intelligence Systems, (HAIS). 2020.
A Machine Consciousness Architecture based on Deep Learning and Gaussian Processes. Eduardo C. Garrido-Merchán, Martín Molina. International Conference on Hybrid Artificial Intelligence Systems, (HAIS). 2020.
2019
Dealing with categorical and integer-valued variables in Bayesian optimization with Gaussian processes. Eduardo C. Garrido Merchán, Daniel Hernández Lobato. Neurocomputing, 2019.
Predictive Entropy Search for Multi-Objective Bayesian Optimization with Constraints. Eduardo C. Garrido Merchán, Daniel Hernández Lobato. Neurocomputing, 2019.
Generating a Question Answering System from Text Causal Relations. Eduardo C. Garrido Merchán, Cristina Puente Agueda, Jose A. Olivas, Alejandro Sobrino. International Conference on Hybrid Artificial Intelligence Systems, (HAIS). 2019.
Heuristic Bayesian Optimization. Luis Carlos Jariego Perez, Eduardo C. Garrido Merchán. Bayesian Inference In Stochastic Processes 2019.
Parallel Predictive Entropy Search for Multiobjective Optimization with Constraints. Eduardo C. Garrido Merchán, Daniel Hernández Lobato. Bayesian Inference In Stochastic Processes 2019.
A Gaussian Process Model for Multi-class Classification with Noisy Inputs. Eduardo C. Garrido Merchán, Bryan Zaldívar, Daniel Hernández Lobato. Bayesian Inference In Stochastic Processes 2019.
Deep Least Squares Fisher Discriminant Analysis. David Díaz Vico, José R. Dorronsoro. IEEE Transactions on Neural Networks and Learning Systems PP(99) DOI: 10.1109/TNNLS.2019.290630. 2019.
Deep Support Vector Classification and Regression. David Díaz Vico, José R. Dorronsoro. International Work-Conference on the Interplay between Natural and Artificial Computation, Volume: IWINAC 2019 Part II, LNCS 11487 proceedings DOI: 10.1007/978-3-030-19651-6_4
Flexible Kernel Selection in MultiTask Support Vector Machines. Carlos Ruiz, Alejandro Catalina, Carlos Aláiz y José R. Dorronsoro. International Joint Conference on Neural Networks (IJCNN). 2019.
A Convex Formulation of SVM-based Multi-Task Learning. Carlos Ruiz, Carlos Aláiz y José R. Dorronsoro. International Conference on Hybrid Artificial Intelligent Systems (HAIS). 2019.
Deep Diffusion Autoencoders. Sara Dorado, Ángela Fernández, José R. Dorronsoro. International Joint Conference on Neural Networks (IJCNN). Budapest, July 2019.
2018
Modular Proximal Optimization for Multidimensional Total-Variation Regularization. Álvaro Barbero and Suvrit Sra. The Journal of Machine Learning Research, Volume 19, Number 56, 1-82.
Improving cash logistics in bank branches by coupling machine learning and robust optimization. Jorge López Lázaro, Álvaro Barbero Jiménez, Akiko Takeda. Expert Syst. Appl. 92: 236-255 (2018)
Deep MLPs for Imbalanced Classification. David Díaz-Vico, Aníbal R. Figueiras-Vidal, José R. Dorronsoro International Joint Conference on Neural Networks
Garrido-Merchán, Eduardo C., Hernández Lobato, D. Dealing with Integer and Categorical-valued Variables in Bayesian Optimization with Gaussian Processes. AutoML workshop. ICML 2018
Garrido-Merchán, Eduardo C. and Albarca, Alejandro. Suggesting Cooking Recipes Through Simulation and Bayesian Optimization. IDEAL: International Conference on Intelligent Data Engineering and Automated Learning 2018
Córdoba, Irene and Garrido-Merchán, Eduardo C. and Hernández-Lobato, Daniel and Bielza, Concha and Larrañaga, Pedro. Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks. CAEPIA: Conferencia de la Asociación Española para la Inteligencia Artificial 2018
Catalina, Alejandro and Alaíz, Carlos M. and Dorronsoro, José Ramón, Accelerated Block Coordinate Descent for Sparse Group Lasso, International Joint Conference on Neural Networks 2018
Díaz-Vico, David and Figueiras-Vidal, Aníbal R. and Dorronsoro, José Ramón. Deep MLPs for Imbalanced Classification. International Joint Conference on Neural Networks. 2018
Prada, Jesús and Dorronsoro, José Ramón. General noise support vector regression with non-constant uncertainty intervals for solar radiation prediction. Journal of Modern Power Systems and Clean Energy Volume 6, Number 2. 268-280. ISSN 2196-5420. [ DOI | http ]
Torres-Barrán, Alberto and Alaíz, Carlos M. and Dorronsoro, José Ramón. v-SVM solutions of constrained Lasso and Elastic net Neurocomputing Volume 275, 1921-1931. ISSN 0925-2312. [ DOI | http ]
Maryam Sabzevari, Gonzalo Martínez-Muñoz, Alberto Suárez, Vote-boosting ensembles, Pattern Recognition Volume 83, 119-133. 2018. ISSN 0031-3203. [ DOI | http ]. Keywords: Ensemble learning; Boosting; Uncertainty-based emphasis; Robust classification
Maryam Sabzevari and Gonzalo Martínez-Muñoz and Alberto Suárez, A two-stage ensemble method for the detection of class-label noise, Neurocomputing Volume 275, 2374-2383. 2018
Maryam Sabzevari and Gonzalo Martínez-Muñoz and Alberto Suárez, Vote-boosting ensembles, CoRR Volume 1606.09458, 2016.
Maryam Sabzevari and Gonzalo Martínez-Muñoz and Alberto Suárez, Pooling homogeneous ensembles to build heterogeneous ensembles ArXiv e-prints February 2018.
2017
Torres-Barrán, Alberto and Alonso, Álvaro and Dorronsoro, José Ramón. Regression tree ensembles for wind energy and solar radiation prediction Neurocomputing 2017. ISSN 0925-2312 [ DOI | http ]
Gutiérrez, Pedro Antonio and Pérez-Ortiz, María and Suárez, Alberto. Class Switching Ensembles for Ordinal Regression Proceedings of IWANN 2017, International Work Conference in Artificial Neural Networks 2017. 408-419 [ DOI | http ]
C. Villacampa-Calvo and D. Hernández-Lobato, Scalable Multi-Class Gaussian Process Classification using Expectation Propagation, in Proceedings of the 34th International Conference on Machine Learning, International Convention Centre, Sydney, Australia, 2017, vol. 70.
Jesús Prada and José Dorronsoro, General Noise SVRs and Uncertainty Intervals International Work-Conference on Artificial Neural Networks, IWANN, 2017.
David Díaz-Vico, Alberto Torres-Barrán, Adil Omari, José R. Dorronsoro Deep Neural Networks for Wind and Solar Energy Prediction Neural Processing Letters, Apr 2017
David Díaz-Vico, Adil Omari, Alberto Torres-Barrán, José R. Dorronsoro Deep Fisher Discriminant Analysis International Work-Conference on Artificial Neural Networks, May 2017
A. Catalina and J. R. Dorronsoro. NWP Ensembles for Wind Energy Uncertainty Estimates. Proceedings of the 2017 ECML Workshop on Data Analytics for Renewable Energy Integration. Lecture Notes in Artificial Intelligence 10691, pp. 121-132. Springer Verlag (2017).
A. Catalina, A. Torres, J.R. Dorronsoro. Satellite Based Nowcasting of PV Energy over Peninsular Spain. Proceedings of IWANN 2017, International Work Conference in Neural Networks. Lecture Notes in Computer Science 10305, Springer Verlag, 685-697.
Cornejo-Bueno L., Garrido-Merchán E. C., Hernández-Lobato D. and Salcedo-Sanz S. Bayesian Optimization of a Hybrid System for Robust Ocean Wave Features Prediction. Neurocomputing 2017.
Cornejo-Bueno L., Garrido-Merchán E. C., Hernández-Lobato D., Salcedo-Sanz S. Bayesian Optimization of a Hybrid System for Robust Ocean Wave Energy Prediction. International Work Conference on Artificial Neural Networks, 648-660. 2017.
J. López, Á. Barbero, A. Takeda. Improving cash logistics in bank branches by coupling machine learning and robust optimization. Expert Systems with Applications (Volume 92, February 2018, Pages 236-255), 2017.
2016
Ramon Huerta, Thiago Mosqueiro, Jordi Fonollosa, Nikolai F Rulkov, and Irene Rodriguez-Lujan. Online decorrelation of humidity and temperature in chemical sensors for continuous monitoring. Chemometrics and Intelligent Laboratory Systems, 157:169-176, 2016.
Irene Rodriguez-Lujan, Jeff Hasty, and Ramón Huerta. Fbb: A fast bayesian bound tool to calibrate rna-seq aligners. Bioinformatics, page btw608, 2016.
Alejandro Catalina, Alberto Torres-Barrá and José R. Dorronsoro. Machine Learning Prediction of Photovoltaic Energy from Satellite Sources. Proceedings of the 2016 ECML Workshop on Data Analytics for Renewable Energy Integration. To appear in Lecture Notes in Artificial Intelligence, LNAI, Springer Verlag.
Alberto Torres-Barrán and José R. Dorronsoro. Nesterov Acceleration for the SMO Algorithm, pages 243-250. Springer International Publishing, Cham, 2016. [ DOI | http ]
Soto, Victor and Suárez, Alberto and Martínez-Muñoz, Gonzalo. An Urn Model for Majority Voting in Classification Ensembles. Proceedings of the 30th International Conference on Neural Information Processing Systems 2016. [ http ]
Alberto Torres-Barrán and José R. Dorronsoro. Conjugate descent for the SMO algorithm. In 2016 International Joint Conference on Neural Networks, IJCNN 2016, 2016.
Daniel Hernández-Lobato, Pablo Morales-Mombiela, David Lopez-Paz, and Alberto Suárez. Non-linear causal inference using Gaussianity measures. Journal of Machine Learning Research, 17(28):1-39, 2016.
Daniel Hernández-Lobato, José Miguel Hernández-Lobato, and Zoubin Ghahramani. A probabilistic model for dirty multi-task feature selection. In Proceedings of The 32nd International Conference on Machine Learning, page 1073–1082, 2015.
Viktoriia Sharmanska, Daniel Hernández-Lobato, Jos~Miguel Hernández-Lobato, and Novi Quadrianto. Ambiguity helps: Classification with disagreements in crowdsourced annotations. In IEEE International Conference on Computer Vision and Pattern Recognition, 2016.
Thang Bui, Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Yingzhen Li, and Richard Turner. Deep Gaussian processes for regression using approximate expectation propagation. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2016.
Torrecilla, José L. and Suárez, Alberto. Feature selection in functional data classification with recursive maxima hunting Advances in Neural Information Processing Systems 29 2016. 4835--4843
Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Amar Shah, and Ryan P. Adams. Predictive entropy search for multi-objective Bayesian optimization. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2016.
Yvonne Gala, Angela Fernández, Julia Díaz, José. R. Dorronsoro. Hybrid machine learning forecasting of solar radiation values. Neurocomputing 176 (2016) 48-59.
Angela Fernández, Neta Rabin, Dalia Fishelov, José. R Dorronsoro Auto-adaptative Laplacian Pyramids. Proceedings of the European Symposium in Artificial Neural Networks ESANN 2016.
José Miguel Hernández-Lobato, Yingzhen Li, Mark Rowlan, Thang Bui, Daniel Hernández-Lobato, and Richard Turner. Black-box alpha divergence minimization. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2016.
2015
Bernard R. Lauwerys, Daniel Hernández-Lobato, Pierre Gramme, Julie Ducreux, Adrien Dessy, Isabelle Focant, Jérôme Ambroise, Bertrand Bearzatto, Adrien Nzeusseu Toukap, Benoît J. Van den Eynde, Dirk Elewaut, Jean-Luc Gala, Patrick Durez, Frédéric A. Houssiau, Thibault Helleputte, and Pierre Dupont. Heterogeneity of synovial molecular patterns in patients with arthritis. PLoS ONE, 10(4):1-18, 2015.
Daniel Hernández-Lobato and José Miguel Hernández-Lobato. Scalable Gaussian process classification via expectation propagation. In Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, page 168–176, 2015.
Carlos M Alaíz, Alvaro Barbero, and José R Dorronsoro. Enforcing group structure through the group fused lasso. In Artificial Neural Networks, pages 349-371. Springer International Publishing, 2015.
Alvaro Barbero, Akiko Takeda, and Jorge López. Geometric intuition and algorithms for ev-svm. The Journal of Machine Learning Research, 16(1):323-369, 2015.
Alberto Torres-Barrán and José R. Dorronsoro. Conjugate descent for the minimum norm problem. In NIPS Workshop on Optimization for Machine Learning, 2015.
David Díaz, Alberto Torres, and José R. Dorronsoro. Advances in Computational Intelligence: 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, Palma de Mallorca, Spain, June 10-12, 2015. Proceedings, Part I, chapter Deep Neural Networks for Wind Energy Prediction, pages 430-443. Springer International Publishing, Cham, 2015. [ DOI | http ]
Carlos Alaíz, Alberto Torres, and José R. Dorronsoro. Solving constrained lasso and elastic net using ν-svms. In Proceedings of ESANN 2015, Bruges, Belgium, 22-24 April 2015, pages 1382-1390, 2015.
Álvaro Alonso, Alberto Torres, and José R. Dorronsoro. Hybrid Artificial Intelligent Systems: 10th International Conference, HAIS 2015, Bilbao, Spain, June 22-24, 2015, Proceedings, chapter Random Forests and Gradient Boosting for Wind Energy Prediction, pages 26-37. Springer International Publishing, Cham, 2015. [ DOI | http ]
Irene Rodríguez-Luján and Ramón Huerta. A fisher consistent multiclass loss function with variable margin on positive examples. Electron. J. Statist., 9(2):2255-2292, 2015. [ DOI ]
Maryam Sabzevari, Gonzalo Martínez-Muñoz, and Alberto Suárez. Small margin ensembles can be robust to class-label noise. Neurocomputing, 2015.
Daniel Hernández-Lobato, Ioannis Katakis, Gonzalo Martínez-Muñoz, and Ioannis Partalas. Special issue on solving complex machine learning problems with ensemble methods Neurocomputing, 150:402-403, 2015.
José Miguel Hernández-Lobato, Daniel Hernández-Lobato, and Alberto Suárez. Expectation propagation in linear regression models with spike-and-slab priors. Machine Learning, pages 1-51, 2014.
2014
Jordi Fonollosa, Irene Rodriguez-Lujan, Abhijit V Shevade, Margie L Homer, Margaret A Ryan, and Ramón Huerta. Human activity monitoring using gas sensor arrays. Sensors and Actuators B: Chemical, 199:398-402, 2014.
Jordi Fonollosa, Irene Rodríguez-Luján, Marco Trincavelli, Alexander Vergara, and Ramón Huerta. Chemical discrimination in turbulent gas mixtures with mox sensors validated by gas chromatography-mass spectrometry. Sensors, 14(10):19336-19353, 2014.
Víctor Soto, Sergio García-Moratilla, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, and Alberto Suárez. A double pruning scheme for boosting ensembles. IEEE T. Cybernetics, 44(12):2682-2695, 2014.
José Miguel Hernández-Lobato, Neil Houlsby, and Zoubin Ghahramani. Probabilistic matrix factorization with non-random missing data. In Proceedings of the 31th International Conference on Machine Learning, ICML 2014, Beijing, China, 21-26 June 2014, pages 1512-1520, 2014.
Maryam Sabzevari, Gonzalo Martínez-Muñoz, and Alberto Suárez. Improving the robustness of bagging with reduced sampling size. In 22th European Symposium on Artificial Neural Networks, ESANN 2014, Bruges, Belgium, April 23-25, 2014.
Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting, Christoph H Lampert, and Novi Quadrianto. Mind the nuisance: Gaussian process classification using privileged noise. In Advances in Neural Information Processing Systems, pages 837-845, 2014.
Irene Rodriguez-Lujan, Jordi Fonollosa, Alexander Vergara, Margie Homer, and Ramon Huerta. On the calibration of sensor arrays for pattern recognition using the minimal number of experiments. Chemometrics and Intelligent Laboratory Systems, 130:123-134, 2014.
L.F. Lago-Fernández, J. Aragón, G. Martínez-Muñoz, A.M. González, and M. Sánchez-Montañés. Cluster validation in problems with increasing dimensionality and unbalanced clusters. Neurocomputing, 123:33-39, 2014. [ http ]
Ángela Fernández, Neta Rabin, Ronald R. Coifman, and Joseph Eckstein. Diffusion methods for aligning medical data: Location prediction in CT scan images. Medical Image Analysis, 18(2):425-432, January 2014. [ DOI | http ]
Alberto Torres, Jesús Prada, and José R. Dorronsoro. Nowcasting meteorological readings for wind energy prediction. In EWEA 2014, 2014.
Alberto Torres, David Díaz, and José R. Dorronsoro. Sparse one hidden layer mlps. In Proceedings of ESANN 2014, Bruges, Belgium, 23-25 April 2015, pages 655-660, 2014.
2013
Lorenzo Hernández, Jorge Tejero, Alberto Suárez, and Santiago Carrillo-Menéndez. Percentiles of sums of heavy-tailed random variables: beyond the single-loss approximation. Statistics and Computing, 24(3):377-397, 2013.
Lorenzo Hernandez, Jorge Tejero, Alberto Suarez, and Santiago Carrillo-Menendez. Closed-form approximations for operational value-at-risk. Journal of Operational Risk, 8(4):39-54, 2013.
Alejandro Llorente and Alberto Suárez. Critical sample size for the l p-norm estimator in linear regression models. In Proceedings of the 2013 Winter Simulation Conference: Simulation: Making Decisions in a Complex World, pages 1047-1056, 2013.
José Miguel Hernández-Lobato, James R Lloyd, and Daniel Hernández-Lobato. Gaussian process conditional copulas with applications to financial time series. In C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger, editors, Advances in Neural Information Processing Systems 26, pages 1736-1744. 2013.
Daniel Hernández-Lobato and José Miguel Hernández-Lobato. Learning feature selection dependencies in multi-task learning. In C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger, editors, Advances in Neural Information Processing Systems 26, pages 746-754. 2013.
D. Hernández-Lobato, G. Martínez-Muñoz, and A. Suáarez. How large should ensembles of classifiers be? Pattern Recognition, 46(5):1323-1336, 2013.
P. Morales-Mombiela, D. Hernández-Lobato, and A. Suárez. Statistical tests for the detection of the arrow of time in vector autoregressive models. pages 1544-1550, 2013.
D. Hernández-Lobato, J.M. Hernández-Lobato, and P. Dupont. Generalized spike-and-slab priors for bayesian group feature selection using expectation propagation. Journal of Machine Learning Research, 14:1891-1945, 2013.
Carlos M. Alaíz, Francesco Dinuzzo, and Suvrit Sra. Correlation matrix nearness and completion under observation uncertainty. IMA Journal of Numerical Analysis, December 2013. [ DOI | http ]
Hind Azegrouz, Gopal Karemore, Alberto Torres, Carlos M. Alaíz, Ana M. Gonzalez, Pedro Nevado, Álvaro Salmerón, Teijo Pellinen, Miguel Á. del Pozo, José R. Dorronsoro, and María C. Montoya. Cell-based fuzzy metrics enhance high content screening (hcs) assay robustness. Journal of Biomolecular Screening, 18(10):1270-1283, December 2013. [ DOI | http ]
Ángela Fernández, Calos M. Alaíz, Ana M. González, Julia Díaz, and José R. Dorronsoro. Local anisotropic diffusion detection of wind ramps. Neural Information Processing Systems, NIPS 2013 Workshop: Machine Learning for Sustainability, 2013. [ http ]
Carlos M. Alaíz, Álvaro Barbero, and José R. Dorronsoro. Group fused lasso. In Valeri Mladenov, Günther Palm, Alessandro Villa, Bruno Apolloni, Petia Koprinkova-Hristova, and Nikola Kasabov, editors, Artificial Neural Networks and Machine Learning - ICANN 2013, volume 8131 of Lecture Notes in Computer Science, pages 66-73, Heidelberg, Germany, September 2013. ENNS, Springer-Verlag GmbH. [ DOI | www: ]
Yvonne Gala, Ángela Fernández, Julia Díaz, and José R. Dorronsoro. Support vector forecasting of solar radiation values. In Jeng-Shyang Pan, Marios M. Polycarpou, MichalWoŹniak, André C.P.L.F. Carvalho, Héctor Quintián, and Emilio Corchado, editors, Hybrid Artificial Intelligent Systems, HAIS 2013, volume 8073 of Lecture Notes in Computer Science, pages 51-60, Heidelberg, Germany, September 2013. Springer Berlin Heidelberg. [ DOI | http ]
D. Hernández-Lobato, G. Martínez-Muñoz, and A. Suárez. How large should ensembles of classifiers be? Pattern Recognition, 46(5):1323-1336, 2013. [ http ]
Irene Rodriguez-Lujan, Gonzalo Bailador, Carmen Sanchez-Avila, Ana Herrero, and Guillermo Vidal-de Miguel. Analysis of pattern recognition and dimensionality reduction techniques for odor biometrics. Knowledge-Based Systems, 52:279-289, 2013.
Ángela Fernández, Calos M. Alaíz, Ana M. González, Julia Díaz, and José R. Dorronsoro. Diffusion maps for wind power ramp detection. In Ignacio Rojas, Gonzalo Joya, and Joan Gabestany, editors, Advances in Computational Intelligence – IWANN 2013, volume 7902 of Lecture Notes in Computer Science, pages 106-113. Springer Berlin Heidelberg, 2013. [ DOI ]
Javier Di Deco, Ana M. Gonzalez, Julia Diaz, Virginia Mato, Daniel Garcia–Frank, Juan Alvarez–Linera, Ana Frank, and Juan A. Hernandez–Tamames. Machine learning and social network analysis applied to alzheimer's disease biomarkers. Current Topics in Medicinal Chemistry, 13:652-662, 2013. [ DOI | http ]
2012
Vicente Torres-Costa, Gonzalo Martínez-Muñoz, Vanessa Sánchez-Vaquero, Álvaro Muñoz-Noval, Laura González-Méndez, Esther Punzón-Quijorna, Darío Gallach-Pérez, Miguel Manso-Silván, Aurelio Climent-Font, Josefa P García-Ruiz, et al. Engineering of silicon surfaces at the micro-and nanoscales for cell adhesion and migration control. International journal of nanomedicine, 7:623, 2012.
Alberto Suárez, Robert Silbey, and Irwin Oppenheim. Phase transition in the jarzynski estimator of free energy differences. Phys. Rev. E, 85:051108, May 2012. [ DOI | http ]
Jiahao Chen, Eric Hontz, Jeremy Moix, Matthew Welborn, Troy Van Voorhis, Alberto Suárez, Ramis Movassagh, and Alan Edelman. Error analysis of free probability approximations to the density of states of disordered systems. Phys. Rev. Lett., 109:036403, Jul 2012. [ DOI | http ]
J. López and J.R. Dorronsoro. Simple Proof of Convergence of the SMO Algorithm for Different SVM Variants. IEEE Transactions on Neural Networks and Learning Systems, 23:1142-1147, 2012. [ DOI ]
J. López and J.R. Dorronsoro. The Convergence Rate of the MDM Algorithm. In International Joint Conference on Neural Networks (IJCNN'12), pages 1-7, 2012. [ DOI ]
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, and Alberto Suárez. On the independence of the individual predictions in parallel randomizedensembles. In European Symposium on Artificial Neural Networks, pages 233-238, 2012.
Daniel Hernández-Lobato, Gonzalo Martínez-Mu noz, and Alberto Suárez. How large should ensembles of classifiers be? Pattern Recognition, 46(5):1323 - 1336, 2013.
Ángela Fernández, Calos M. Alaíz, Ana M. González, Julia Díaz, and José R. Dorronsoro. Diffusion maps and local models for wind power prediction. In Artificial Neural Networks and Machine Learning – ICANN 2012. ICANN, September 2012. [ DOI | .pdf ]
Carlos M. Alaíz, Alberto Torres, and José R. Dorronsoro. Sparse linear wind farm energy forecast. In Alessandro Villa, Wlodzislaw Duch, Péter Érdi, Francesco Masulli, and Günther Palm, editors, Artificial Neural Networks and Machine Learning – ICANN 2012, volume 7553 of Lecture Notes in Computer Science, pages 557-564, Heidelberg, Germany, September 2012. ENNS, Springer-Verlag GmbH. [ DOI | .pdf ]
Carlos M. Alaíz, Álvaro Barbero, and José R. Dorronsoro. Sparse methods for wind energy prediction. In The 2012 International Joint Conference on Neural Networks (IJCNN), pages 1-7, Washington, D.C., U.S.A., June 2012. IEEE Computational Intelligence Society, IEEE Xplore. [ DOI | http ]
Ángela Fernández, Ana M. González, Julia Díaz, and José R. Dorronsoro. Diffusion maps for the description of meteorological data. In International Conference on Hybrid Artificial Intelligence Systems, HAIS 2012, Salamanca, Spain, March 28-30, 2012, On Line Proceedings. HAIS, March 2012. [ DOI | http ]
Irene Rodriguez-Lujan, Carlos Santa Cruz, and Ramon Huerta. Hierarchical linear support vector machine. Pattern Recognition, 45(12):4414 - 4427, 2012. [ DOI | http ]
2011
Jorge López, Álvaro Barbero, and José R. Dorronsoro. Clipping algorithms for solving the nearest point problem over reduced convex hulls. Pattern Recognition , September 2010. [ DOI | http ]
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, and Alberto Suárez. Inference on the prediction of ensembles of infinite size. Pattern Recognition , 44(7):1426-1434, July 2011. [ DOI | http ]
Jose Miguel Hernández-Lobato, Daniel Hernández-Lobato, and Alberto Suárez. Network-based sparse Bayesian classification. Pattern Recognition , October 2010. [ DOI | http ]
Álvaro Barbero and Suvrit Sra. Fast newton-type methods for total variation regularization. Proceedings of the 28th International Conference on Machine Learning, 2011.
Daniel Hernández-Lobato, José Miguel Hernández-Lobato, and Pierre Dupont. Advances in neural information processing systems, 24. In J. Shawe-Taylor, R. Zemel, P. Bartlett, F. Pereira, and K Weinberger, editors, Advances in Neural Information Processing Systems, 24 , pages 280-288, 2011.
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, and Alberto Suárez. Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles. Neurocomputing , 74(12-13):2250-2264, June 2011. [ DOI | http ]
Álvaro Barbero and José R. Dorronsoro. Cycle-breaking acceleration for support vector regression. Neurocomputing , 74(16):2649-2656, September 2011. [ DOI | http ]
I. Rodriguez-Lujan, C. Santa Cruz, and R. Huerta. On the Equivalence of Kernel Fisher Discriminant Analysis and Kernel Quadratic Programming Feature Selection. Pattern Recognition Letters , April 2011. [ DOI | http ]
Jorge López and Johan Suykens. First and Second Order SMO Algorithms for LS-SVM Classifiers. Neural Processing Letters , pages 1-14, December 2010. [ DOI | http ]
David Delgado-Gómez, David Aguado, Jorge Lopez-Castroman, Carlos Santacruz, and Antonio Artés-Rodriguez. Improving sale performance prediction using support vector machines. Expert Systems with Applications , 38(5):5129 - 5132, 2011. [ DOI | http ]
Carlos Aguirre, Pedro Pascual, Doris Campos, and Eduardo Serrano. Single neuron transient activity detection by means of tomography. BMC Neuroscience , 12(Suppl 1):P297, 2011. [ DOI | http ]
Alejandro Sierra Carmen Garcia, Vicente Ponsoda. Prediction of item psychometric indices from item characteristics automatically extracted from the stem and option text. International Journal of Continuing Engineering Education and Life-Long Learning , 21(2/3):210 - 221, 2011. [ DOI ]
A. Barbero and J.R. Dorronsoro. Momentum sequential minimal optimization: An accelerated method for support vector machine training. In Neural Networks (IJCNN), The 2011 International Joint Conference on , pages 370 -377, 31 2011-aug. 5 2011. [ DOI ]
J. Lopez and J.R. Dorronsoro. Convergence of algorithms for solving the nearest point problem in reduced convex hulls. In Neural Networks (IJCNN), The 2011 International Joint Conference on , pages 413 -420, 31 2011-aug. 5 2011. [ DOI ]
José Miguel Hernández-Lobato, Pablo Morales-Mombiela, and Alberto Suárez. Gaussianity measures for detecting the direction of causal time series. In Toby Walsh, editor, IJCAI , pages 1318-1323. IJCAI/AAAI, 2011. [ http ]
Jorge López, Álvaro Barbero, and José R. Dorronsoro. Momentum acceleration of least-squares support vector machines. In Proceedings of the 21st international conference on Artificial neural networks - Volume Part II , ICANN'11, pages 135-142, Berlin, Heidelberg, 2011. Springer-Verlag. [ http ]
Jorge López Lázaro, Kris De Brabanter, José R. Dorronsoro, and Johan A. K. Suykens. Sparse ls-svms with l0 - norm minimization. In ESANN , 2011.
Carlos Aguirre, Pedro Pascual, Doris Campos, and Eduardo Serrano. Single neuron transient activity detection by means of tomography. In Joan Cabestany, Ignacio Rojas, and Gonzalo Joya, editors, Advances in Computational Intelligence , volume 6691 of Lecture Notes in Computer Science , pages 49-56. Springer Berlin / Heidelberg, 2011. 10.1007/978-3-642-21501-8_7. [ http ]
E. Korutcheva K. Koroutchev. Figures design for surface coding with orientation. In 14th International Workshop on Combinatorial Image Analysis, Robust Multi-Class Gaussian Process Classification , 2011.
R.N. Rojas-Bello, L.F. Lago-Fernandez, G. Martinez-Mufioz, and M.A. Sanchez-Montanes. A comparison of techniques for robust gender recognition. In Image Processing (ICIP), 2011 18th IEEE International Conference on , pages 561 -564, sept. 2011. [ DOI ]
Rubén Ruíz-Torrubiano and Alberto Suárez. The transrar crossover operator for genetic algorithms with set encoding. In Proceedings of the 13th annual conference on Genetic and evolutionary computation , GECCO '11, pages 489-496, New York, NY, USA, 2011. ACM. [ DOI | http ]
A.M. González Luis F. Lago-Fernández, G. Martínez-Muñoz and Manuel Sánchez-Montañes. Evaluation of negentropy-based cluster validation techniques in problems with increasing dimensionality. In International Conference on Pattern Recognition (ICPRAM) 2012 , 2012.
Carlos M. Alaíz and José R. Dorronsoro. On the learning of esn linear readouts. In José A. Lozano, José A. Gámez, and Moreno José A., editors, Advances in Artificial Intelligence , volume 7023 of Lecture Notes in Computer Science , pages 124-133, Heidelberg, Germany, November 2011. AEPIA, Springer-Verlag GmbH.
2010
Álvaro Barbero and José R. Dorronsoro. Faster directions for second order smo. In Lecture Notes in Computer Science, volume 6353, pages 30–39, 2010. [pdf]
Álvaro Barbero and Moritz Grosse-Wentrup. Biased feedback in brain-computer interfaces. Journal of Neuroengineering and Rehabilitation, 7(34), July 2010. [pdf]
David Delgado-Gómez, Federico Sukno, David Aguado, Carlos Santacruz, and Antonio Artés-Rodriguez. Individual identification using personality traits. Journal of Network and Computer Applications, 33(3):293–299, 2010. Recent Advances and Future Directions in Biometrics Personal Identification. [pdf]
A. Echeverría and R. Rojas. An evolutionary confidence measure for spotting words in speech recognition. In Proceedings of the 12th Generative Art International Conference. 2009. [pdf]
E. García, A. Rodríguez, M. García, P. Martín, R. Mora, A. López, D. Román, M. García, R. Sanz, J. Díaz, S. Fresnillo, and Á. Valera. Active demand side management operator tool (sgclos) and new communications architecture in the xxi century electrical grid. In CIGRE 2010 (in press), 2010. [pdf]
José Miguel Hernández-Lobato and Alberto Suárez. Robust quantification of the exposure to operational risk: Bringing economic sense to economic capital. In Industrial-Academic Forum on Operational Risk, March 2010. [pdf]
K. Koroutchev and E. Koroutcheva. Statistical Mechanics Approach to Texts. Journal of Entropy, 2010.
J. López and J.R. Dorronsoro. Least 1-Norm SVMs: a New SVM Variant between Standard and LS-SVMs. In Proceedings of the 18th European Symposium on Artificial Neural Networks (ESANN'10), pages 135-140, 2010.[pdf]
J. López, A. Barbero, and J.R. Dorronsoro. An mdm solver for the nearest point problem in scaled convex hulls. In The 2010 International Joint Conference on Neural Networks (IJCNN), pages 1-8, 2010. [pdf]
Jorge López and José R. Dorronsoro. A common framework for the convergence of the gsk, mdm and smo algorithms. In Proceedings of the 20th international conference on Artificial neural networks: Part II, ICANN'10, pages 82-87, Berlin, Heidelberg, 2010. Springer-Verlag. [pdf]
Gonzalo Martínez-Muñoz and Alberto Suárez. Out-of-bag estimation of the optimal sample size in bagging. Pattern Recogn., 43(1):143–152, 2010. [pdf]
Irene Rodriguez-Lujan, Ramon Huerta, Charles Elkan, and Carlos Santa Cruz. Quadratic programming feature selection. Journal of Machine Learning Research, 11:1491−1516, April 2010.[pdf][code]
R. Ruiz-Torrubiano and A. Suarez. Hybrid approaches and dimensionality reduction for portfolio selection with cardinality constraints. Computational Intelligence Magazine, IEEE, 5(2):92–107, may. 2010. [pdf]
Rubén Ruiz-Torrubiano, Sergio García-Moratilla, and Alberto Suárez. Optimization problems with cardinality constraints. In Computational Intelligence in Optimization, volume 7 of Adaptation Learning and Optimization, pages 105–130. Springer Berlin Heidelberg, 2010. 10.1007/978-3-642-12775-5_5. [pdf]
Víctor Soto, Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, and Alberto Suárez. A double pruning algorithm for classification ensembles. In Multiple Classifier Systems, volume 5997 of Lecture Notes in Computer Science, pages 104–113. Springer Berlin / Heidelberg, 2010. 10.1007/978-3-642-12127-2_11. [pdf]
2009
C. Aguirre and P. Pascual. A wavelet based method for detecting multiple encoding rhythms in neural networks. In Lecture Notes in Computer Science: Bio-Inspired Systems: Computational and Ambient Intelligence, pages 9–16, 2009. [pdf]
C. Alaíz, Á. Barbero, Á. Fernández, and J. R. Dorronsoro. High wind and energy specific models for global production forecast. In Proceedings of the 2009 European Wind Energy Conference (EWEC), 2009.
Á. Barbero and J. R. Dorronsoro. A simple maximum gain algorithm for support vector regression. In Lecture Notes in Computer Science, Bio-Inspired systems: Computational and Ambient Intelligence, volume 5517, pages 73–80, 2009. [pdf]
Á. Barbero, M. Franz, W. van Drongelen, J. R. Dorronsoro, B. Schölkopf, and M. Grosse-Wentrup. Implicit wiener series analysis of epileptic seizure recordings. In Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009. [pdf]
Á. Barbero, J. López, and J. R. Dorronsoro. Cycle-breaking Acceleration of SVM Training. Neurocomputing, 72(7-9):1398–1406, 2009. [pdf]
Á. Barbero, J. López, and J. R. Dorronsoro. Finding Optimal Model Parameters by Deterministic and Annealed Focused Grid Search. Neurocomputing, 72(13-15):2824–2832, 2009. [pdf]
J. Díaz, J.R. Dorronsoro, Á Fernández, S. Fresnillo, T. Huelin, and Á Valera. A customer management system for the spanish transport system operator. In Proceedings of the 11th Spanish-Portuguese Conference on Electrical Engineering, 2009.
Ana González, F. Azuaje, J. L. Ramirez, J. F. Da Silveira, and J. R. Dorronsoro. Machine learning techniques for the automated classification of adhesin-like proteins in the human protozoan parasite trypanosoma cruzi. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 5(4):695–702, 2009. [pdf]
D. Hernandez-Lobato, G. Martinez-Muñoz, and A. Suarez. Statistical instance-based pruning in ensembles of independent classifiers. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 31(2):364–369, feb. 2009. [pdf]
José Miguel Hernández-Lobato and Alberto Suárez. Modeling dependence in financial data with semiparametric archimedean copulas. In International Workshop on Advances in Machine Learning for Computational Finance (AMLCF 2009), July 2009. [pdf][videolecture]
K. Koroutchev, E. Koroutcheva, K. Kanev, A. Rodríguez, J. L. Muñiz, and F. Fariñaz. Detection of Unusual Objects and Temporal Patterns in EEG Video Recordings. In Lecture Notes in Computer Science: Advances in Visual Computing, volume 5875, pages 965–974, 2009. [pdf]
K. Koroutchev, E. Koroutcheva, and J. Shen. Statistical Mechanical and Message Passing in Texts. In Proceedings of the 2009 NetStat Conference, 2009.
K. Koroutchev, E. Koroutcheva, and J. Shen. Written Texts as Statistical Mechanical Problem. In Lecture Notes in Computer Science: Advances in Information Retrieval Theory, volume 5766, pages 241–248, 2009. [pdf]
J. López and J. R. Dorronsoro. Rosen’s Projection Method for SVM training. In Proceedings of the 17th European Symposium on Artificial Neural Networks, pages 183–188, 2009.
J. López and J. R. Dorronsoro. A Simple Proof of the Convergence of the SMO Algorithm for Linearly Separable Problems. In Lecture Notes in Computer Science: Artificial Neural Networks - ICANN 2009, volume 5768, pages 904–912, 2009. [pdf]
D. Martín, R. del Toro, R. Haber, and J. R. Dorronsoro. Optimal tuning of a networked linear controller using a multi-objective genetic algorithm and its application to one complex electromechanical process. International Journal of Innovative Computing, Information and Control, 5:3405–3414, 2009. [pdf]
G. Martinez-Muñoz, D. Hernandez-Lobato, and A. Suarez. An analysis of ensemble pruning techniques based on ordered aggregation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 31(2):245–259, feb. 2009. [pdf]
G. Martinez-Muñoz, N. Larios, E. Mortensen, Wei Zhang, A. Yamamuro, R. Paasch, N. Payet, D. Lytle, L. Shapiro, S. Todorovic, A. Moldenke, and T.G. Dietterich. Dictionary-free categorization of very similar objects via stacked evidence trees. In IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009, pages 549–556, jun. 2009. [pdf]
Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, and Alberto Suárez. Statistical instance-based ensemble pruning for multi-class problems. In ICANN ’09: Proceedings of the 19th International Conference on Artificial Neural Networks, pages 90–99, Berlin, Heidelberg, 2009. Springer-Verlag. [pdf]
Y. Nadler, A. M. González, R. L. Camp, D. L. Rimm, H. M. Kluger, and Y. Kluger. Growth factor receptor-bound protein-7 (grb7) as a prognostic marker and therapeutic target in breast cancer. Annals of Oncology, 2009. [pdf]
Alberto Suárez, John Moody, and Matthew Saffell. Dynamic portfolio management with transaction costs. In Multidisciplinary Symposium on Reinforcement Learning (MSRL), June 2009.
Alberto Suárez, John Moody, and Matthew Saffell. Dynamic portfolio management with transaction costs. In International Workshop on Advances in Machine Learning for Computational Finance (AMLCF 2009), July 2009. [pdf][videolecture]
L. Vázquez, S. Jiménez, C. Aguirre, and P. Pascual. Métodos Numéricos para la Física y la Ingeniería. McGraw Hill, 2009.
2008
Á. Barbero, J. López, and J. R. Dorronsoro. A 4–Vector MDM Algorithm for Support Vector Training. In Lecture Notes in Computer Science: Artificial Neural Networks, volume 5165, pages 315–324, Berlin, Heidelberg, 2008. Springer-Verlag. [pdf]
Á. Barbero, J. López, and J. R. Dorronsoro. An Accelerated MDM Algorithm for SVM Training. In Proceedings of the 16th European Symposium on Artificial Neural Networks, pages 421–426, 2008. [pdf]
Á. Barbero, J. López, and J. R. Dorronsoro. Finding Optimal Model Parameters by Discrete Grid Search. In Advances in Soft Computing: Innovations in Hybrid Intelligent Systems, volume 44, pages 120–127. Springer, 2008. [pdf]
Á. Barbero, J. López, and J. R. Dorronsoro. Kernel Methods for Wide Area Wind Generation Forecasting. In Proceedings of the 2008 European Wind Energy Conference (EWEC), 2008.
Ana González and J. R. Dorronsoro. Natural conjugate gradient training of multilayer perceptrons. Neurocomputing, 71:2499–2506, 2008. [pdf]
Daniel Hernández-Lobato. Sparse bayes machines for binary classification. In ICANN ’08: Proceedings of the 18th International Conference on Artificial Neural Networks, Part I, pages 205–214, Berlin, Heidelberg, 2008. Springer-Verlag. [pdf]
Daniel Hernández-Lobato and José Miguel Hernández-Lobato. Bayes machines for binary classification. Pattern Recognition Letters, 29(10):1466–1473, 2008. [pdf]
José Miguel Hernández-Lobato, Tjeerd Dijkstra, and Tom Heskes. Regulator discovery from gene expression time series of malaria parasites: a hierarchical approach. In Advances in Neural Information Processing Systems 20, pages 649–656, Cambridge, MA, 2008. MIT Press. [pdf]
K. Koroutchev and E. Koroutcheva. Detecting the most Unusual Part of a Digital Image. In Proceedings of the 2008 IWCIA Conference, 2008. [pdf]
J. López, Á. Barbero, and J. R. Dorronsoro. On the Equivalence of the SMO and MDM Algorithms for SVM Training. In Lecture Notes in Computer Science: Machine Learning and Knowledge Discovery in Databases, volume 5211, pages 288–300. Springer, 2008. [pdf]
J. López, Á. Barbero, and J. R. Dorronsoro. Simple Clipping Algorithms for Reduced Convex Hull SVM Training. In Lecture Notes in Computer Science: Hybrid Artificial Intelligent Systems, volume 5271, pages 369–377, 2008. [pdf]
Gonzalo Martínez-Muñoz, Aitor Sánchez-Martínez, Daniel Hernández-Lobato, and Alberto Suárez. Class-switching neural network ensembles. Neurocomput., 71(13-15):2521–2528, 2008. [pdf]
Alejandro Sierra Urrecho and Iván Santibáñez Koref. Evolution of descent directions. In Adaptive and Multilevel Metaheuristics, volume 136 of Studies in Computational Intelligence, pages 221–237. Springer Berlin / Heidelberg, 2008. 10.1007/978-3-540-79438-7_11. [pdf]
2007
C. Aguirre, D. Campos, P. Pascual, and L. Vázquez. Pattern formation and encoding rhythms analysis on a spiking-bursting neuronal network. European Physical Journal-Special Topics, 146:169–176, 2007. [pdf]
Á. Barbero, M. S. González-Rodríguez, J. de Lara, and M. Alfonseca. Multi-agent simulation of an educational collaborative web system. In European Simulation and Modelling Conference 2007 proceedings, 2007. [pdf]
Á. Barbero, J. López, and J. R. Dorronsoro. Square Penalty Support Vector Regression. In Lecture Notes in Computer Science: Intelligent Data Engineering and Automated Learning - IDEAL 2007, pages 537–546. Springer, 2007. [pdf]
J. Díaz, M. García, and M. Ramos-Otero. Educational approximation for content creation on a multiplatform ebusiness application. In E-Learn 2007, 2007. [pdf]
J. Díaz, M. García, and M. Ramos-Otero. Unidades mínimas de conocimiento (minimal units of knowledge – umc): A multi-platform ebusiness application example. In IADIS Multiconference on CSIS 2007, 2007.
D. Domínguez, K. Koroutchev, E. Serrano, and F.B. Rodríguez. Information and Topology in Attractor Neural Networks. Neural Computation, 19:956–973, 2007. [pdf]
Daniel García, Ana González, and José R. Dorronsoro. Accelerating kernel perceptron learning. In Proceedings of the ICANN 2007 International Conference in Artificial Neural Networks, Lecture Notes in Computer Science, volume 4668, pages 159–168, 2007. [pdf]
Daniel García, Ana González, and José R. Dorronsoro. Coefficient structure of kernel perceptrons and support vector reduction. In Proceedings of the IWINAC 2007, International Work Conference in Neural Networks, Lecture Notes in Computer Science, volume 4527, pages 337–345, 2007. [pdf]
Ana González and J. R. Dorronsoro. Natural learning in nlda networks. Neural Networks, 20:610–620, 2007. [pdf]
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, and Alberto Suárez. Out of bootstrap estimation of generalization error curves in bagging ensembles. In IDEAL’07: Proceedings of the 8th International Conference on Intelligent Data Engineering and Automated Learning, pages 47–56, Berlin, Heidelberg, 2007. Springer-Verlag. [pdf]
José Miguel Hernández-Lobato, Daniel Hernández-Lobato, and Alberto Suárez. Garch processes with non-parametric innovations for market risk estimation. In ICANN’07: Proceedings of the 17th International Conference on Artificial Neural Networks, pages 718–727, Berlin, Heidelberg, 2007. Springer-Verlag. [pdf]
K. Koroutchev and E. Koroutcheva. Bump Formations in Attractor Neural Network and their Application to Image Reconstruction. In AIP Conference Proceedings, volume 887, pages 242–248, 2007. [pdf]
K. Koroutchev and E. Koroutcheva. Statistical Mechanics of Bump Formations in Neural Networks. In Proceedings of the Conference and Research Workshop: Perspectives on Nonlinear Dynamics, 2007.
K. Koroutchev and E. Koroutcheva. Statistical Mechanics of Texts. In Proceedings of Common Concepts in Statistical Physics and Computer Science, 2007.
Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, and Alberto Suárez. Selection of decision stumps in bagging ensembles. In ICANN’07: Proceedings of the 17th International Conference on Artificial Neural Networks, pages 319–328, Berlin, Heidelberg, 2007. Springer-Verlag. [pdf]
2006
C. Aguirre, D. Campos, P. Pascual, and E. Serrano. Synchronization effects using a piecewise linear map-based spiking-bursting neuron model. Neurocomputing, 69:1116–1119, 2006. [pdf]
C. Aguirre, D. Campos, P. Pascual, and L. Vázquez. Computer simulations for a fractional calculus derived internet traffic model. In Proceedings of the 5th Conference on Engineering Computational Technology, Civil-Comp, pages 45–46, 2006. [pdf]
C. Aguirre, D. Campos, P. Pascual, and L. Vázquez. Pattern formation and encoding rhythms analysis on a spiking-bursting neuronal network. European Physical Journal-Special Topics, 146:169–176, 2007. [pdf]
Daniel García, Ana González, and José R. Dorronsoro. Convex perceptrons. In Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2006. Lecture Notes in Computer Science, volume 4131, pages 169–177, 2006. [pdf]
Sergio García-Moratilla, Gonzalo Martínez-Muñoz, and Alberto Suárez. Evaluation of decision tree pruning with subadditive penalties. In IDEAL’06: Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning, volume 4224 of Lecture Notes in Computer Science, pages 995–1002. Springer Berlin / Heidelberg, 2006. 10.1007/11875581_119. [pdf]
Ana González and José R. Dorronsoro. Natural conjugate gradient training of multilayer perceptrons. In Lecture Notes in Computer Science, volume 4131, pages 169–177, 2006. [pdf]
Ana González and José R. Dorronsoro. A note on conjugate natural gradient training of multilayer perceptrons. In Proceedings of the 2006 International Joint Conference in Neural Networks, 2006. [pdf]
K. Koroutchev and M. Cebrián. Detecting the Same Text in Different Languages. In Proceedings of the 2006 IEEE Information Theory Workshop, pages 337–341, 2006. [pdf]
K. Koroutchev and J. R. Dorronsoro. Factorization and structure of natural 4 x 4 patch densities. Optical Engineering, 45:12–24, 2006.
K. Koroutchev and E. Koroutcheva. Bump Formation in a Binary Attractor Neural Network. Physical Review E, 73(11), 2006. [pdf]
K. Koroutchev and E. Koroutcheva. Improved Storage Capacity of Hebbian Learning Attractor Neural Networks with Bump Formations. In Lecture Notes in Computer Science: Artificial Neural Networks - ICANN 2006, volume 4131, pages 234–243, 2006. [pdf]
Kostadin Koroutchev and Manuel Cebrián. Detecting translations of the same text and data with common source. Journal of Statistical Mechanics: Theory and Experiment, 2006(10), 2006. [pdf]
2005
C. Aguirre, D. Campos, P. Pascual, and E. Serrano. A model of spiking-bursting neuronal behavior using a piecewise linear twodimensional map. In Lecture Notes in Computer Science: 8th International Work-Conference on Artificial Neural Networks - IWANN 2005, pages 130–135, Berlin, Heidelberg, 2005. Springer-Verlag. [pdf]
C. Aguirre, D. Campos, P. Pascual, and E. Serrano. Neuronal behavior with sub-threshold oscillations and spiking/bursting activity using a piecewise linear two-dimensional map. In Lecture Notes in Computer Science: Artificial Neural Networks: Biological Inspirations – ICANN 2005, pages 103–108, Berlin, Heidelberg, 2005. Springer-Verlag. [pdf]
C. Aguirre, D. Campos, P. Pascual, and E. Serrano. Synchronization effects using a piecewise linear map-based spiking-bursting neuron. In Proceedings of the 14th Annual Computational Neuroscience Meeting, pages 94–94, 2005. [pdf]
Iván Cantador and José R. Dorronsoro. Balanced boosting with parallel perceptrons. In Lecture Notes in Computer Science, volume 3512, pages 208–216, 2005. [pdf]
Iván Cantador and José R. Dorronsoro. Boosting parallel perceptrons for label noise reduction in classification problems. In Lecture Notes in Computer Science, volume 3562, pages 586–593, 2005. [pdf]
Iván Cantador and José R. Dorronsoro. Parallel perceptrons, activation margins and imbalanced training set pruning. In Lecture Notes in Computer Science, volume 3523, pages 43–50, 2005. [pdf]
G. G. de Rivera, R. Ribalda, K. Koroutchev, J. Colás, and J. Garrido. Hardware Independent Architecture for Autonomous Collaborative Agents. In Proceedings of the 2nd International Conference on Informatics in Control, Automation and Robotics, 2005.
J. Díaz. Desarrollo de competencias en la comunidad universitaria. El ’Espacio Innovador’ y la Red, pages 46–52, 2005.
Ana González, Iván Cantador, and José R. Dorronsoro. Discriminant parallel perceptrons. In Lecture Notes in Computer Science, volume 3697, pages 15–20, 2005. [pdf]
K. Koroutchev and E. Koroutcheva. Conditions for the Emergence of Spatially Asymmetric Retrieval States in Attractor Neural Network. Central European Journal of Physics, 3(3):409–419, 2005. [pdf]
K. Koroutchev and E. Koroutcheva. Spatial Asymmetric Retrieval States in binary Attractor Neural Networks. In Proceedings of the conference ”Fluctuation in Noise”, volume 780, pages 603–606. American Institute of Physics, 2005. [pdf]
K. Koroutchev, F. B. Rodríguez, and C. Miravet. Superresolution by Using Codebook. In Proceedings of the International Conference on Multimedia, Image Processing and Computer Vision, 2005.
Others
Daniel Hernández-Lobato, José Miguel Hernández-Lobato, and Alberto Suárez. Expectation propagation for microarray data classification. Submitted for publication, 2010.
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, and Alberto Suárez. How large should ensembles of classifiers be? Submitted for publication, 2009.
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, and Alberto Suárez. Inference on the asymptotic prediction of classification ensembles. Submitted for publication, 2010.
Daniel Hernández-Lobato, Gonzalo Martínez-Muñoz, and Alberto Suárez. Pruning regression bagging ensembles. Submitted for publication, 2010.
José Miguel Hernández-Lobato and Alberto Suárez. Semiparametric archimedean copulas. Submitted for publication, 2010.
K. Koroutchev and E. Koroutcheva. Text as Statistical Mechanics Object. Technical Report IC/IR/002, ICTP, 2007. [pdf]
K. Koroutchev and E. Koroutcheva. Detection of Rare Parts in Video. Technical Report IC-009, ICTP, 2009.
J. López and J. A. K. Suykens. First and Second Order SMO Algorithms for Large Scale LS-SVM training. Technical Report 09-179, Katholieke Universiteit Leuven, 2009.
J. López. On the relationship among the mdm, smo and svm-light algorithms for training support vector machines. Master's thesis, Escuela Politécnica Superior de la Universidad Autónoma de Madrid, 2008. [pdf]