Daniel Hernández-Lobato
TitleCited byYear
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
2742008
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
852016
Black-box α-divergence minimization
JM Hernández-Lobato, Y Li, M Rowland, D Hernández-Lobato, T Bui, ...
International Machine Learning Society, 2016
842016
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
802013
How large should ensembles of classifiers be?
D Hernández-Lobato, G MartíNez-MuñOz, A Suárez
Pattern Recognition 46 (5), 1323-1336, 2013
512013
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
502008
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
452016
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
442011
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
382015
Robust multi-class Gaussian process classification
D Hernández-Lobato, JM Hernández-Lobato, P Dupont
Advances in neural information processing systems, 280-288, 2011
362011
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
342006
Class-switching neural network ensembles
G Martínez-Muñoz, A Sánchez-Martínez, D Hernández-Lobato, A Suárez
Neurocomputing 71 (13-15), 2521-2528, 2008
292008
Expectation propagation for microarray data classification
D Hernández-Lobato, JM Hernández-Lobato, A Suárez
Pattern recognition letters 31 (12), 1618-1626, 2010
282010
Scalable Gaussian process classification via expectation propagation
D Hernández-Lobato, JM Hernández-Lobato
Artificial Intelligence and Statistics, 168-176, 2016
272016
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
262014
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
242010
Network-based sparse Bayesian classification
JM Hernández-Lobato, D Hernández-Lobato, A Suárez
Pattern Recognition 44 (4), 886-900, 2011
222011
Learning feature selection dependencies in multi-task learning
D Hernández-Lobato, JM Hernández-Lobato
Advances in Neural Information Processing Systems, 746-754, 2013
212013
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
202015
Pruning adaptive boosting ensembles by means of a genetic algorithm
D Hernández-Lobato, JM Hernández-Lobato, R Ruiz-Torrubiano, Á Valle
International Conference on Intelligent Data Engineering and Automated …, 2006
202006
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Articles 1–20