Daniel Hernández-Lobato - Google Scholar

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	All	Since 2015
Citations	1555	1188
h-index	20	18
i10-index	35	29

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20082009201020112012201320142015201620172018201920208 27 33 51 55 84 96 120 169 218 233 284 157

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José Miguel Hernández-LobatoUniversity Lecturer (US Assistant Professor) University of CambridgeVerified email at cam.ac.uk
Alberto SuárezProfessor of Artificial Intelligence, Computer Science Department, Universidad Autónoma de MadridVerified email at uam.es
Gonzalo Martínez MuñozUniversidad Autónoma de MadridVerified email at uam.es
Richard E TurnerUniversity Reader, University of CambridgeVerified email at cam.ac.uk
Thang D BuiResearch Scientist, Uber AI; Lecturer, University of SydneyVerified email at sydney.edu.au
Yingzhen LiMicrosoft Research CambridgeVerified email at cam.ac.uk
Pierre DupontProfessor of Computer Science, ICTEAM, EPL, Université catholique de LouvainVerified email at uclouvain.be
Eduardo C. Garrido-MerchánTeaching Assistant at Universidad Autonoma de MadridVerified email at uam.es
Ryan P. AdamsPrinceton UniversityVerified email at princeton.edu
Novi QuadriantoReader in Machine Learning, Predictive Analytics Lab (PAL), University of SussexVerified email at sussex.ac.uk
Amar ShahPhD student, University of CambridgeVerified email at cam.ac.uk
Mark RowlandResearch Scientist, DeepMindVerified email at google.com
Lauwerys BUniversité catholique de Louvain, Institut de Recherche Expérimentale et Clinique, Pôle deVerified email at uclouvain.be
Viktoriia SharmanskaImperial College Research FellowVerified email at imperial.ac.uk
Víctor SotoColumbia UniversityVerified email at cs.columbia.edu
Houssiau FAProfesseur; IREC, SSS, Université catholique de LouvainVerified email at uclouvain.be
Julie DucreuxChargé de Recherche, Université catholique de LouvainVerified email at uclouvain.be
Carlos Villacampa-CalvoUniversidad Autónoma de MadridVerified email at uam.es
Zoubin GhahramaniProfessor, University of Cambridge, and Chief Scientist, UberVerified email at eng.cam.ac.uk
Laura Cornejo-BuenoAssistant Professor, Rey Juan Carlos UniversityVerified email at urjc.es

Daniel Hernández-Lobato

Lecturer of Computer Science, Unviersidad Autónoma de Madrid

Verified email at uam.es - Homepage

Machine Learning - Bayesian Models - Feature Selection - Kernel Methods - Approximate Inference - Gaussian Processes - Ensemble


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An analysis of ensemble pruning techniques based on ordered aggregation G Martínez-Muñoz, D Hernández-Lobato, A Suárez IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (2), 245-259, 2008	303	2008
Deep Gaussian processes for regression using approximate expectation propagation T Bui, D Hernández-Lobato, J Hernandez-Lobato, Y Li, R Turner International conference on machine learning, 1472-1481, 2016	125	2016
Black-box alpha divergence minimization J Hernandez-Lobato, Y Li, M Rowland, T Bui, D Hernández-Lobato, ... International Conference on Machine Learning, 1511-1520, 2016	120	2016
Generalized spike-and-slab priors for Bayesian group feature selection using expectation propagation D Hernández-Lobato, JM Hernández-Lobato, P Dupont The Journal of Machine Learning Research 14 (1), 1891-1945, 2013	91	2013
Predictive entropy search for multi-objective bayesian optimization D Hernández-Lobato, J Hernandez-Lobato, A Shah, R Adams International Conference on Machine Learning, 1492-1501, 2016	78	2016
How large should ensembles of classifiers be? D Hernández-Lobato, G MartíNez-MuñOz, A Suárez Pattern Recognition 46 (5), 1323-1336, 2013	60	2013
Statistical instance-based pruning in ensembles of independent classifiers D Hernández-Lobato, G Martínez-Muñoz, A Suárez IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (2), 364-369, 2008	56	2008
Robust multi-class Gaussian process classification D Hernández-Lobato, JM Hernández-Lobato, P Dupont Advances in neural information processing systems, 280-288, 2011	51	2011
Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles D Hernández-Lobato, G Martínez-Muñoz, A Suárez Neurocomputing 74 (12-13), 2250-2264, 2011	46	2011
Expectation propagation in linear regression models with spike-and-slab priors JM Hernández-Lobato, D Hernández-Lobato, A Suárez Machine Learning 99 (3), 437-487, 2015	45	2015
Scalable gaussian process classification via expectation propagation D Hernández-Lobato, JM Hernández-Lobato Artificial Intelligence and Statistics, 168-176, 2016	42	2016
Pruning in ordered regression bagging ensembles D Hernández-Lobato, G Martínez-Muñoz, A Suárez The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006	37	2006
Dealing with categorical and integer-valued variables in bayesian optimization with gaussian processes EC Garrido-Merchán, D Hernández-Lobato Neurocomputing 380, 20-35, 2020	31	2020
Mind the nuisance: Gaussian process classification using privileged noise D Hernández-Lobato, V Sharmanska, K Kersting, CH Lampert, ... Advances in Neural Information Processing Systems, 837-845, 2014	31	2014
Expectation propagation for microarray data classification D Hernández-Lobato, JM Hernández-Lobato, A Suárez Pattern recognition letters 31 (12), 1618-1626, 2010	31	2010
Class-switching neural network ensembles G Martínez-Muñoz, A Sánchez-Martínez, D Hernández-Lobato, A Suárez Neurocomputing 71 (13-15), 2521-2528, 2008	29	2008
Expectation propagation for Bayesian multi-task feature selection D Hernández-Lobato, JM Hernández-Lobato, T Helleputte, P Dupont Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010	26	2010
Learning feature selection dependencies in multi-task learning D Hernández-Lobato, JM Hernández-Lobato Advances in Neural Information Processing Systems, 746-754, 2013	24	2013
Heterogeneity of synovial molecular patterns in patients with arthritis BR Lauwerys, D Hernández-Lobato, P Gramme, J Ducreux, A Dessy, ... PloS one 10 (4), e0122104, 2015	23	2015
Network-based sparse Bayesian classification JM Hernández-Lobato, D Hernández-Lobato, A Suárez Pattern recognition 44 (4), 886-900, 2011	22	2011

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