Robust-multi-task gradient boosting.

Daniel Hernández-Lobato Universidad Autónoma de Madrid, Computer Science Department, Spain https://orcid.org/0000-0001-5845-437X https://www.wikidata.org/entity/Q83096529 https://www.researcherid.com/rid/E-8337-2012 https://publons.com/researcher/2727364

Seyedsaman Emami Gonzalo Martínez-Muñoz Daniel Hernández-Lobato Robust-multi-task gradient boosting. 130696 2026 303 Expert Syst. Appl. https://doi.org/10.1016/j.eswa.2025.130696 db/journals/eswa/eswa303.html#EmamiMH26 streams/journals/eswa

Luis A. Ortega 0001 Simón Rodríguez Santana Daniel Hernández-Lobato Scalable Linearized Laplace Approximation via Surrogate Neural Kernel. 2026 January abs/2601.21835 CoRR https://doi.org/10.48550/arXiv.2601.21835 db/journals/corr/corr2601.html#abs-2601-21835 streams/journals/corr

Pedro Jiménez Luis A. Ortega 0001 Pablo Morales-Álvarez Daniel Hernández-Lobato Improving the Linearized Laplace Approximation via Quadratic Approximations. 2026 February abs/2602.03394 CoRR https://doi.org/10.48550/arXiv.2602.03394 db/journals/corr/corr2602.html#abs-2602-03394 streams/journals/corr

Seyedsaman Emami Daniel Hernández-Lobato Gonzalo Martínez-Muñoz Robust multi-task boosting using clustering and local ensembling. 2026 February abs/2602.14231 CoRR https://doi.org/10.48550/arXiv.2602.14231 db/journals/corr/corr2602.html#abs-2602-14231 streams/journals/corr

Daniel Fernández-Sánchez Daniel Hernández-Lobato Joint entropy search for multi-objective Bayesian optimization with constraints and multiple fidelities. 131674 2025 657 Neurocomputing https://doi.org/10.1016/j.neucom.2025.131674 db/journals/ijon/ijon657.html#FernandezSanchezH25 streams/journals/ijon

Daniel Fernández-Sánchez Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Alpha entropy search for new information-based Bayesian optimization. 113612 2025 322 Knowl. Based Syst. https://doi.org/10.1016/j.knosys.2025.113612 db/journals/kbs/kbs322.html#FernandezSanchezGH25 streams/journals/kbs

Seyedsaman Emami Gonzalo Martínez-Muñoz Daniel Hernández-Lobato Robust-Multi-Task Gradient Boosting. 2025 July abs/2507.11411 CoRR https://doi.org/10.48550/arXiv.2507.11411 db/journals/corr/corr2507.html#abs-2507-11411 streams/journals/corr

Daniel Fernández-Sánchez Daniel Hernández-Lobato Joint Entropy Search for Multi-objective Bayesian Optimization with Constraints and Multiple Fidelities. 2024 ESANN https://doi.org/10.14428/esann/2024.ES2024-24 conf/esann/2024 db/conf/esann/esann2024.html#Fernandez-Sanchez24 Luis A. Ortega Andrés Simón Rodríguez Santana Daniel Hernández-Lobato Variational Linearized Laplace Approximation for Bayesian Deep Learning. 2024 ICML https://proceedings.mlr.press/v235/ortega24a.html https://openreview.net/forum?id=1n3aC5rvdE conf/icml/2024 db/conf/icml/icml2024.html#AndresSH24 38815-38836

Daniel Fernández-Sánchez Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Alpha Entropy Search for New Information-based Bayesian Optimization. 2024 abs/2411.16586 CoRR https://doi.org/10.48550/arXiv.2411.16586 db/journals/corr/corr2411.html#abs-2411-16586 streams/journals/corr

Luis A. Ortega 0001 Simón Rodríguez Santana Daniel Hernández-Lobato Fixed-Mean Gaussian Processes for Post-hoc Bayesian Deep Learning. 2024 abs/2412.04177 CoRR https://doi.org/10.48550/arXiv.2412.04177 db/journals/corr/corr2412.html#abs-2412-04177 streams/journals/corr

Eduardo C. Garrido-Merchán Daniel Fernández-Sánchez Daniel Hernández-Lobato Parallel predictive entropy search for multi-objective Bayesian optimization with constraints applied to the tuning of machine learning algorithms. 119328 2023 April 215 Expert Syst. Appl. https://doi.org/10.1016/j.eswa.2022.119328 db/journals/eswa/eswa215.html#GarridoMerchanFH23

Daniel Fernández-Sánchez Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Improved max-value entropy search for multi-objective bayesian optimization with constraints. 126290 2023 546 Neurocomputing https://doi.org/10.1016/j.neucom.2023.126290 db/journals/ijon/ijon546.html#Fernandez-Sanchez23

Bahram Jafrasteh Daniel Hernández-Lobato Simón Pedro Lubián-López Isabel Benavente-Fernández Gaussian processes for missing value imputation. 110603 2023 273 Knowl. Based Syst. https://doi.org/10.1016/j.knosys.2023.110603 db/journals/kbs/kbs273.html#JafrastehHLB23

Daniel Heestermans Svendsen Daniel Hernández-Lobato Luca Martino Valero Laparra Álvaro Moreno-Martínez Gustau Camps-Valls Inference over radiative transfer models using variational and expectation maximization methods. 921-937 2023 March 112 Mach. Learn. 3 https://doi.org/10.1007/s10994-021-05999-4 https://www.wikidata.org/entity/Q112833056 db/journals/ml/ml112.html#SvendsenHMLMC23

Luis A. Ortega 0001 Simón Rodríguez Santana Daniel Hernández-Lobato Deep Variational Implicit Processes. 2023 ICLR https://openreview.net/forum?id=8aeSJNbmbQq conf/iclr/2023 db/conf/iclr/iclr2023.html#OrtegaSH23 Juan Maroñas Daniel Hernández-Lobato Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification. 24045-24081 2023 ICML https://proceedings.mlr.press/v202/maronas23a.html conf/icml/2023 db/conf/icml/icml2023.html#MaronasH23

Luis A. Ortega 0001 Simón Rodríguez Santana Daniel Hernández-Lobato Variational Linearized Laplace Approximation for Bayesian Deep Learning. 2023 abs/2302.12565 CoRR https://doi.org/10.48550/arXiv.2302.12565 db/journals/corr/corr2302.html#abs-2302-12565

Francisco Javier Sáez-Maldonado Juan Maroñas Daniel Hernández-Lobato Deep Transformed Gaussian Processes. 2023 abs/2310.18230 CoRR https://doi.org/10.48550/arXiv.2310.18230 db/journals/corr/corr2310.html#abs-2310-18230

Carlos Villacampa-Calvo Gonzalo Hernández-Muñoz Daniel Hernández-Lobato Alpha-divergence minimization for deep Gaussian processes. 139-171 2022 150 Int. J. Approx. Reason. https://doi.org/10.1016/j.ijar.2022.08.003 https://www.wikidata.org/entity/Q114171978 db/journals/ijar/ijar150.html#Villacampa-Calvo22

Simón Rodríguez Santana Daniel Hernández-Lobato Adversarial α-divergence minimization for Bayesian approximate inference. 260-274 2022 471 Neurocomputing https://doi.org/10.1016/j.neucom.2020.09.076 db/journals/ijon/ijon471.html#SantanaH22

Bahram Jafrasteh Carlos Villacampa-Calvo Daniel Hernández-Lobato Input Dependent Sparse Gaussian Processes. 9739-9759 2022 ICML https://proceedings.mlr.press/v162/jafrasteh22a.html conf/icml/2022 db/conf/icml/icml2022.html#JafrastehVH22 Simón Rodríguez Santana Bryan Zaldivar Daniel Hernández-Lobato Function-space Inference with Sparse Implicit Processes. 18723-18740 2022 ICML https://proceedings.mlr.press/v162/rodri-guez-santana22a.html conf/icml/2022 db/conf/icml/icml2022.html#SantanaZH22

Daniel Heestermans Svendsen Daniel Hernández-Lobato Luca Martino Valero Laparra Álvaro Moreno Gustau Camps-Valls Inference over radiative transfer models using variational and expectation maximization methods. 2022 abs/2204.03346 CoRR https://doi.org/10.48550/arXiv.2204.03346 db/journals/corr/corr2204.html#abs-2204-03346

Bahram Jafrasteh Daniel Hernández-Lobato Simón Pedro Lubián-López Isabel Benavente-Fernández Gaussian Processes for Missing Value Imputation. 2022 abs/2204.04648 CoRR https://doi.org/10.48550/arXiv.2204.04648 db/journals/corr/corr2204.html#abs-2204-04648

Juan Maroñas Daniel Hernández-Lobato Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification. 2022 abs/2205.15008 CoRR https://doi.org/10.48550/arXiv.2205.15008 db/journals/corr/corr2205.html#abs-2205-15008

Luis A. Ortega 0001 Simón Rodríguez Santana Daniel Hernández-Lobato Deep Variational Implicit Processes. 2022 abs/2206.06720 CoRR https://doi.org/10.48550/arXiv.2206.06720 db/journals/corr/corr2206.html#abs-2206-06720

Simón Rodríguez Santana Luis A. Ortega Andrés Daniel Hernández-Lobato Bryan Zaldivar Correcting Model Bias with Sparse Implicit Processes. 2022 abs/2207.10673 CoRR https://doi.org/10.48550/arXiv.2207.10673 db/journals/corr/corr2207.html#abs-2207-10673

Carlos Villacampa-Calvo Bryan Zaldivar Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Multi-class Gaussian Process Classification with Noisy Inputs. 36:1-36:52 2021 22 J. Mach. Learn. Res. https://jmlr.org/papers/v22/20-107.html db/journals/jmlr/jmlr22.html#Villacampa-Calvo21

Pablo Morales-Alvarez Daniel Hernández-Lobato Rafael Molina 0001 José Miguel Hernández-Lobato Activation-level uncertainty in deep neural networks. 2021 ICLR https://openreview.net/forum?id=UvBPbpvHRj- conf/iclr/2021 db/conf/iclr/iclr2021.html#Morales-Alvarez21

Bahram Jafrasteh Carlos Villacampa-Calvo Daniel Hernández-Lobato Input Dependent Sparse Gaussian Processes. 2021 abs/2107.07281 CoRR https://arxiv.org/abs/2107.07281 db/journals/corr/corr2107.html#abs-2107-07281

Simón Rodríguez Santana Bryan Zaldivar Daniel Hernández-Lobato Sparse Implicit Processes for Approximate Inference. 2021 abs/2110.07618 CoRR https://arxiv.org/abs/2110.07618 db/journals/corr/corr2110.html#abs-2110-07618

Carlos Villacampa-Calvo Daniel Hernández-Lobato Alpha divergence minimization in multi-class Gaussian process classification. 210-227 2020 378 Neurocomputing https://doi.org/10.1016/j.neucom.2019.09.090 db/journals/ijon/ijon378.html#Villacampa-Calvo20

Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Dealing with categorical and integer-valued variables in Bayesian Optimization with Gaussian processes. 20-35 2020 380 Neurocomputing https://doi.org/10.1016/j.neucom.2019.11.004 db/journals/ijon/ijon380.html#Garrido-Merchan20

Marta Gómez-Sancho Daniel Hernández-Lobato Importance Weighted Adversarial Variational Bayes. 374-386 2020 HAIS https://doi.org/10.1007/978-3-030-61705-9_31 conf/hais/2020 db/conf/hais/hais2020.html#Gomez-SanchoH20 Gonzalo Hernández-Muñoz Carlos Villacampa-Calvo Daniel Hernández-Lobato Deep Gaussian Processes Using Expectation Propagation and Monte Carlo Methods. 479-494 2020 ECML/PKDD (3) https://doi.org/10.1007/978-3-030-67664-3_29 conf/pkdd/2020-3 db/conf/pkdd/pkdd2020-3.html#Hernandez-Munoz20

Carlos Villacampa-Calvo Bryan Zaldivar Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Multi-class Gaussian Process Classification with Noisy Inputs. 2020 abs/2001.10523 CoRR https://arxiv.org/abs/2001.10523 db/journals/corr/corr2001.html#abs-2001-10523

Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Parallel Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints. 2020 abs/2004.00601 CoRR https://arxiv.org/abs/2004.00601 db/journals/corr/corr2004.html#abs-2004-00601

Daniel Fernández-Sánchez Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Max-value Entropy Search for Multi-objective Bayesian Optimization with Constraints. 2020 abs/2011.01150 CoRR https://arxiv.org/abs/2011.01150 db/journals/corr/corr2011.html#abs-2011-01150

Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints. 50-68 2019 361 Neurocomputing https://doi.org/10.1016/j.neucom.2019.06.025 db/journals/ijon/ijon361.html#Garrido-Merchan19

Daniel Hernández-Lobato Pablo Morales-Mombiela David Lopez-Paz Alberto Suárez 0001 Non-linear Causal Inference Using Gaussianity Measures. 257-299 2019 Cause Effect Pairs in Machine Learning https://doi.org/10.1007/978-3-030-21810-2_8 books/sp/19/GSB2019 db/books/collections/GSB2019.html#Hernandez-LobatoML019

Simón Rodríguez Santana Daniel Hernández-Lobato Adversarial α-divergence Minimization for Bayesian Approximate Inference. 2019 abs/1909.06945 CoRR http://arxiv.org/abs/1909.06945 db/journals/corr/corr1909.html#abs-1909-06945

Laura Cornejo-Bueno Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Sancho Salcedo-Sanz Bayesian optimization of a hybrid system for robust ocean wave features prediction. 818-828 2018 275 Neurocomputing https://doi.org/10.1016/j.neucom.2017.09.025 db/journals/ijon/ijon275.html#Cornejo-BuenoGH18

Irene Córdoba Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Concha Bielza Pedro Larrañaga Bayesian Optimization of the PC Algorithm for Learning Gaussian Bayesian Networks. 44-54 2018 CAEPIA https://doi.org/10.1007/978-3-030-00374-6_5 conf/caepia/2018 db/conf/caepia/caepia2018.html#CordobaGHBL18

Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Dealing with Categorical and Integer-valued Variables in Bayesian Optimization with Gaussian Processes. 2018 abs/1805.03463 CoRR http://arxiv.org/abs/1805.03463 db/journals/corr/corr1805.html#abs-1805-03463

Irene Córdoba-Sánchez Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Concha Bielza Pedro Larrañaga Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks. 2018 abs/1806.11015 CoRR http://arxiv.org/abs/1806.11015 db/journals/corr/corr1806.html#abs-1806-11015

Carlos Villacampa-Calvo Daniel Hernández-Lobato Scalable Multi-Class Gaussian Process Classification using Expectation Propagation. 3550-3559 2017 ICML http://proceedings.mlr.press/v70/villacampa-calvo17a.html conf/icml/2017 db/conf/icml/icml2017.html#Villacampa-Calvo17 Laura Cornejo-Bueno Eduardo C. Garrido-Merchán Daniel Hernández-Lobato Sancho Salcedo-Sanz Bayesian Optimization of a Hybrid Prediction System for Optimal Wave Energy Estimation Problems. 648-660 2017 IWANN (1) https://doi.org/10.1007/978-3-319-59153-7_56 conf/iwann/2017-1 db/conf/iwann/iwann2017-1.html#Cornejo-BuenoGH17

Daniel Hernández-Lobato Pablo Morales-Mombiela David Lopez-Paz Alberto Suárez 0001 Non-linear Causal Inference using Gaussianity Measures. 28:1-28:39 2016 17 J. Mach. Learn. Res. https://jmlr.org/papers/v17/14-375.html db/journals/jmlr/jmlr17.html#Hernandez-Lobato16

Daniel Hernández-Lobato José Miguel Hernández-Lobato Scalable Gaussian Process Classification via Expectation Propagation. 168-176 2016 AISTATS http://proceedings.mlr.press/v51/hernandez-lobato16.html conf/aistats/2016 db/conf/aistats/aistats2016.html#Hernandez-Lobato16 Viktoriia Sharmanska Daniel Hernández-Lobato José Miguel Hernández-Lobato Novi Quadrianto Ambiguity Helps: Classification with Disagreements in Crowdsourced Annotations. 2194-2202 2016 CVPR https://doi.org/10.1109/CVPR.2016.241 https://doi.ieeecomputersociety.org/10.1109/CVPR.2016.241 conf/cvpr/2016 db/conf/cvpr/cvpr2016.html#SharmanskaHHQ16 Thang D. Bui Daniel Hernández-Lobato José Miguel Hernández-Lobato Yingzhen Li Richard E. Turner Deep Gaussian Processes for Regression using Approximate Expectation Propagation. 1472-1481 2016 ICML http://proceedings.mlr.press/v48/bui16.html conf/icml/2016 db/conf/icml/icml2016.html#BuiHHLT16 Daniel Hernández-Lobato José Miguel Hernández-Lobato Amar Shah 0001 Ryan P. Adams Predictive Entropy Search for Multi-objective Bayesian Optimization. 1492-1501 2016 ICML http://proceedings.mlr.press/v48/hernandez-lobatoa16.html conf/icml/2016 db/conf/icml/icml2016.html#Hernandez-Lobato16 José Miguel Hernández-Lobato Yingzhen Li Mark Rowland 0001 Thang D. Bui Daniel Hernández-Lobato Richard E. Turner Black-Box Alpha Divergence Minimization. 1511-1520 2016 ICML http://proceedings.mlr.press/v48/hernandez-lobatob16.html conf/icml/2016 db/conf/icml/icml2016.html#Hernandez-Lobato16a

Thang D. Bui Daniel Hernández-Lobato Yingzhen Li José Miguel Hernández-Lobato Richard E. Turner Deep Gaussian Processes for Regression using Approximate Expectation Propagation. 2016 abs/1602.04133 CoRR http://arxiv.org/abs/1602.04133 db/journals/corr/corr1602.html#BuiHLHT16

Daniel Hernández-Lobato Ioannis Katakis 0001 Gonzalo Martínez-Muñoz Ioannis Partalas Special Issue on "Solving complex machine learning problems with ensemble methods". 402-403 2015 150 Neurocomputing https://doi.org/10.1016/j.neucom.2014.09.038 db/journals/ijon/ijon150.html#Hernandez-LobatoKMP15

José Miguel Hernández-Lobato Daniel Hernández-Lobato Alberto Suárez 0001 Expectation propagation in linear regression models with spike-and-slab priors. 437-487 2015 99 Mach. Learn. 3 https://doi.org/10.1007/s10994-014-5475-7 db/journals/ml/ml99.html#Hernandez-Lobato15

Daniel Hernández-Lobato José Miguel Hernández-Lobato Zoubin Ghahramani A Probabilistic Model for Dirty Multi-task Feature Selection. 1073-1082 2015 ICML http://proceedings.mlr.press/v37/hernandez-lobatoa15.html conf/icml/2015 db/conf/icml/icml2015.html#Hernandez-Lobato15

Víctor Soto Sergio García-Moratilla Gonzalo Martínez-Muñoz Daniel Hernández-Lobato Alberto Suárez 0001 A Double Pruning Scheme for Boosting Ensembles. 2682-2695 2014 44 IEEE Trans. Cybern. 12 https://doi.org/10.1109/TCYB.2014.2313638 https://www.wikidata.org/entity/Q43710278 db/journals/tcyb/tcyb44.html#SotoGMHS14

Daniel Hernández-Lobato Viktoriia Sharmanska Kristian Kersting Christoph H. Lampert Novi Quadrianto Mind the Nuisance: Gaussian Process Classification using Privileged Noise. 837-845 2014 NIPS https://proceedings.neurips.cc/paper/2014/hash/6e2713a6efee97bacb63e52c54f0ada0-Abstract.html http://papers.nips.cc/paper/5373-mind-the-nuisance-gaussian-process-classification-using-privileged-noise conf/nips/2014 db/conf/nips/nips2014.html#Hernandez-LobatoSKLQ14

Daniel Hernández-Lobato José Miguel Hernández-Lobato Pierre Dupont Generalized spike-and-slab priors for Bayesian group feature selection using expectation propagation. 1891-1945 2013 14 J. Mach. Learn. Res. 1 https://dl.acm.org/doi/10.5555/2567709.2567724 db/journals/jmlr/jmlr14.html#Hernandez-LobatoHD13

Daniel Hernández-Lobato Gonzalo Martínez-Muñoz Alberto Suárez 0001 How large should ensembles of classifiers be? 1323-1336 2013 46 Pattern Recognit. 5 https://doi.org/10.1016/j.patcog.2012.10.021 db/journals/pr/pr46.html#Hernandez-LobatoMS13

Pablo Morales-Mombiela Daniel Hernández-Lobato Alberto Suárez 0001 Statistical Tests for the Detection of the Arrow of Time in Vector Autoregressive Models. 2013 IJCAI http://www.aaai.org/ocs/index.php/IJCAI/IJCAI13/paper/view/6715 http://ijcai.org/Abstract/13/230 conf/ijcai/2013 db/conf/ijcai/ijcai2013.html#Morales-MombielaHS13 1544-1550 Daniel Hernández-Lobato José Miguel Hernández-Lobato Learning Feature Selection Dependencies in Multi-task Learning. 746-754 2013 NIPS https://proceedings.neurips.cc/paper/2013/hash/75fc093c0ee742f6dddaa13fff98f104-Abstract.html http://papers.nips.cc/paper/5212-learning-feature-selection-dependencies-in-multi-task-learning conf/nips/2013 db/conf/nips/nips2013.html#Hernandez-LobatoH13 José Miguel Hernández-Lobato James Robert Lloyd Daniel Hernández-Lobato Gaussian Process Conditional Copulas with Applications to Financial Time Series. 1736-1744 2013 NIPS https://proceedings.neurips.cc/paper/2013/hash/67d16d00201083a2b118dd5128dd6f59-Abstract.html http://papers.nips.cc/paper/5084-gaussian-process-conditional-copulas-with-applications-to-financial-time-series conf/nips/2013 db/conf/nips/nips2013.html#Hernandez-LobatoLH13 Daniel Hernández-Lobato Gonzalo Martínez-Muñoz Alberto Suárez 0001 On the Independence of the Individual Predictions in Parallel Randomized Ensembles. 2012 ESANN https://www.esann.org/sites/default/files/proceedings/legacy/es2012-19.pdf conf/esann/2012 db/conf/esann/esann2012.html#Hernandez-LobatoMS12

Daniel Hernández-Lobato Gonzalo Martínez-Muñoz Alberto Suárez 0001 Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles. 2250-2264 2011 74 Neurocomputing 12-13 https://doi.org/10.1016/j.neucom.2011.03.001 db/journals/ijon/ijon74.html#Hernandez-LobatoMS11

José Miguel Hernández-Lobato Daniel Hernández-Lobato Alberto Suárez 0001 Network-based sparse Bayesian classification. 886-900 2011 44 Pattern Recognit. 4 https://doi.org/10.1016/j.patcog.2010.10.016 db/journals/pr/pr44.html#Hernandez-LobatoHS11

Daniel Hernández-Lobato Gonzalo Martínez-Muñoz Alberto Suárez 0001 Inference on the prediction of ensembles of infinite size. 1426-1434 2011 44 Pattern Recognit. 7 https://doi.org/10.1016/j.patcog.2010.12.021 db/journals/pr/pr44.html#Hernandez-LobatoMS11

Daniel Hernández-Lobato José Miguel Hernández-Lobato Pierre Dupont Robust Multi-Class Gaussian Process Classification. 280-288 2011 NIPS https://proceedings.neurips.cc/paper/2011/hash/7eabe3a1649ffa2b3ff8c02ebfd5659f-Abstract.html http://papers.nips.cc/paper/4241-robust-multi-class-gaussian-process-classification conf/nips/2011 db/conf/nips/nips2011.html#Hernandez-LobatoHD11

Daniel Hernández-Lobato José Miguel Hernández-Lobato Alberto Suárez 0001 Expectation Propagation for microarray data classification. 1618-1626 2010 31 Pattern Recognit. Lett. 12 https://doi.org/10.1016/j.patrec.2010.05.007 db/journals/prl/prl31.html#Hernandez-LobatoHS10

Víctor Soto Gonzalo Martínez-Muñoz Daniel Hernández-Lobato Alberto Suárez 0001 A Double Pruning Algorithm for Classification Ensembles. 104-113 2010 MCS https://doi.org/10.1007/978-3-642-12127-2_11 conf/mcs/2010 db/conf/mcs/mcs2010.html#SotoMHS10 Daniel Hernández-Lobato José Miguel Hernández-Lobato Thibault Helleputte Pierre Dupont Expectation Propagation for Bayesian Multi-task Feature Selection. 522-537 2010 ECML/PKDD (1) https://doi.org/10.1007/978-3-642-15880-3_39 conf/pkdd/2010-1 db/conf/pkdd/pkdd2010-1.html#Hernandez-LobatoHHD10

Gonzalo Martínez-Muñoz Daniel Hernández-Lobato Alberto Suárez 0001 An Analysis of Ensemble Pruning Techniques Based on Ordered Aggregation. 245-259 2009 31 IEEE Trans. Pattern Anal. Mach. Intell. 2 https://doi.org/10.1109/TPAMI.2008.78 http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.78 https://www.wikidata.org/entity/Q51858963 db/journals/pami/pami31.html#Martinez-MunozHS09

Daniel Hernández-Lobato Gonzalo Martínez-Muñoz Alberto Suárez 0001 Statistical Instance-Based Pruning in Ensembles of Independent Classifiers. 364-369 2009 31 IEEE Trans. Pattern Anal. Mach. Intell. 2 https://doi.org/10.1109/TPAMI.2008.204 http://doi.ieeecomputersociety.org/10.1109/TPAMI.2008.204 https://www.wikidata.org/entity/Q33396050 db/journals/pami/pami31.html#Hernandez-LobatoMS09

Gonzalo Martínez-Muñoz Daniel Hernández-Lobato Alberto Suárez 0001 Statistical Instance-Based Ensemble Pruning for Multi-class Problems. 90-99 2009 ICANN (1) https://doi.org/10.1007/978-3-642-04274-4_10 conf/icann/2009-1 db/conf/icann/icann2009-1.html#Martinez-MunozHS09

Gonzalo Martínez-Muñoz Aitor Sánchez-Martínez Daniel Hernández-Lobato Alberto Suárez 0001 Class-switching neural network ensembles. 2521-2528 2008 71 Neurocomputing 13-15 https://doi.org/10.1016/j.neucom.2007.11.041 db/journals/ijon/ijon71.html#Martinez-MunozSHS08

Daniel Hernández-Lobato José Miguel Hernández-Lobato Bayes Machines for binary classification. 1466-1473 2008 29 Pattern Recognit. Lett. 10 https://doi.org/10.1016/j.patrec.2008.02.022 db/journals/prl/prl29.html#Hernandez-LobatoH08

Daniel Hernández-Lobato Sparse Bayes Machines for Binary Classification. 205-214 2008 ICANN (1) https://doi.org/10.1007/978-3-540-87536-9_22 conf/icann/2008-1 db/conf/icann/icann2008-1.html#Hernandez-Lobato08 Gonzalo Martínez-Muñoz Daniel Hernández-Lobato Alberto Suárez 0001 Selection of Decision Stumps in Bagging Ensembles. 319-328 2007 conf/icann/2007-1 ICANN (1) https://doi.org/10.1007/978-3-540-74690-4_33 db/conf/icann/icann2007-1.html#Martinez-MunozHS07 José Miguel Hernández-Lobato Daniel Hernández-Lobato Alberto Suárez 0001 GARCH Processes with Non-parametric Innovations for Market Risk Estimation. 718-727 2007 conf/icann/2007-2 ICANN (2) https://doi.org/10.1007/978-3-540-74695-9_74 db/conf/icann/icann2007-2.html#Hernandez-LobatoHS07 Daniel Hernández-Lobato Gonzalo Martínez-Muñoz Alberto Suárez 0001 Out of Bootstrap Estimation of Generalization Error Curves in Bagging Ensembles. 47-56 2007 conf/ideal/2007 IDEAL https://doi.org/10.1007/978-3-540-77226-2_6 db/conf/ideal/ideal2007.html#Hernandez-LobatoMS07 Gonzalo Martínez-Muñoz Aitor Sánchez-Martínez Daniel Hernández-Lobato Alberto Suárez 0001 Building Ensembles of Neural Networks with Class-Switching. 178-187 2006 conf/icann/2006-1 ICANN (1) https://doi.org/10.1007/11840817_19 db/conf/icann/icann2006-1.html#Martinez-MunozSHS06 Daniel Hernández-Lobato José Miguel Hernández-Lobato Rubén Ruiz-Torrubiano Ángel Valle Pruning Adaptive Boosting Ensembles by Means of a Genetic Algorithm. 322-329 2006 conf/ideal/2006 IDEAL https://doi.org/10.1007/11875581_39 db/conf/ideal/ideal2006.html#Hernandez-LobatoHRV06 Daniel Hernández-Lobato Gonzalo Martínez-Muñoz Alberto Suárez 0001 Pruning in Ordered Regression Bagging Ensembles. 1266-1273 2006 IJCNN https://doi.org/10.1109/IJCNN.2006.246837 conf/ijcnn/2006 db/conf/ijcnn/ijcnn2006.html#Hernandez-LobatoMS06 Ryan P. Adams Isabel Benavente-Fernández Concha Bielza Thang D. Bui Gustau Camps-Valls Irene Córdoba-SánchezIrene Córdoba Laura Cornejo-Bueno Pierre Dupont Seyedsaman Emami Daniel Fernández-Sánchez Sergio García-Moratilla Eduardo C. Garrido-Merchán Zoubin Ghahramani Marta Gómez-Sancho Thibault Helleputte José Miguel Hernández-Lobato Gonzalo Hernández-Muñoz Bahram Jafrasteh Pedro Jiménez Ioannis Katakis 0001 Kristian Kersting Christoph H. Lampert Valero Laparra Pedro Larrañaga Yingzhen Li James Robert Lloyd David Lopez-Paz Simón Pedro Lubián-López Gonzalo Martínez-Muñoz Luca Martino Juan Maroñas MolanoJuan Maroñas Rafael Molina 0001 Pablo Morales-AlvarezPablo Morales-Álvarez Pablo Morales-Mombiela Álvaro Moreno-MartínezÁlvaro Moreno Luis A. Ortega 0001Luis A. Ortega Andrés Ioannis Partalas Novi Quadrianto Mark Rowland 0001 Rubén Ruiz-Torrubiano Francisco Javier Sáez-Maldonado Sancho Salcedo-Sanz Aitor Sánchez-Martínez Simón Rodríguez Santana Amar Shah 0001 Viktoriia Sharmanska Víctor Soto Alberto Suárez 0001 Daniel H. SvendsenDaniel Heestermans Svendsen Richard E. Turner Ángel Valle Carlos Villacampa-Calvo Bryan Zaldivar