Jerónimo Hernández-González
Jerónimo Hernández-González
Post-doc researcher, IIIA-CSIC
Dirección de correo verificada de iiia.csic.es - Página principal
TítuloCitado porAño
Weak supervision and other non-standard classification problems: a taxonomy
J Hernández-González, I Inza, JA Lozano
Pattern Recognition Letters 69, 49-55, 2016
672016
Learning Bayesian network classifiers from label proportions
J Hernández-González, I Inza, JA Lozano
Pattern Recognition 46 (12), 3425-3440, 2013
442013
Learning to classify software defects from crowds: a novel approach
J Hernández-González, D Rodríguez, I Inza, R Harrison, JA Lozano
Applied Soft Computing 62, 579-591, 2018
102018
Fitting the data from embryo implantation prediction: Learning from label proportions
J Hernández-González, I Inza, L Crisol-Ortíz, MA Guembe, MJ Iñarra, ...
Statistical methods in medical research 27 (4), 1056-1066, 2018
92018
Multidimensional learning from crowds: Usefulness and application of expertise detection
J Hernández‐González, I Inza, JA Lozano
International Journal of Intelligent Systems 30 (3), 326-354, 2015
82015
Learning naive Bayes models for multiple-instance learning with label proportions
J Hernández, I Inza
Conference of the Spanish Association for Artificial Intelligence, 134-144, 2011
82011
A novel weakly supervised problem: Learning from positive-unlabeled proportions
J Hernández-González, I Inza, JA Lozano
Conference of the Spanish Association for Artificial Intelligence, 3-13, 2015
52015
Learning from proportions of positive and unlabeled examples
J Hernández‐González, I Inza, JA Lozano
International Journal of Intelligent Systems 32 (2), 109-133, 2017
42017
Similarity networks for heterogeneous data
LA Belanche Muñoz, J Hernández González
ESANN 2012: the 20th European Symposium on Artificial Neural Networks …, 2012
3*2012
Beach litter forecasting on the south-eastern coast of the Bay of Biscay: A bayesian networks approach
I Granado, OC Basurko, A Rubio, L Ferrer, J Hernández-González, ...
Continental Shelf Research 180, 14-23, 2019
22019
A note on the behavior of majority voting in multi-class domains with biased annotators
J Hernández-González, I Inza, JA Lozano
IEEE Transactions on Knowledge and Data Engineering 31 (1), 195-200, 2018
22018
Weak Labeling for Crowd Learning
I Benaran-Munoz, J Hernández-González, A Pérez
ArXiv e-prints, 2018
22018
Learning from crowds in multi-dimensional classification domains
J Hernández-González, I Inza, JA Lozano
Conference of the Spanish Association for Artificial Intelligence, 352-362, 2013
22013
Aggregated outputs by linear models: An application on marine litter beaching prediction
J Hernández-González, I Inza, I Granado, OC Basurko, JA Fernandes, ...
Information Sciences 481, 381-393, 2019
12019
Evaluation in learning from label proportions: An approximation to the precision-recall curve
J Hernández-González
Conference of the Spanish Association for Artificial Intelligence, 76-86, 2018
12018
Two datasets of defect reports labeled by a crowd of annotators of unknown reliability
J Hernández-González, D Rodriguez, I Inza, R Harrison, JA Lozano
Data in brief 18, 840-845, 2018
12018
Merging knowledge bases in different languages
J Hernández-González, ER Hruschka Jr, T Mitchell
Proceedings of TextGraphs-11: the Workshop on Graph-based Methods for …, 2017
12017
A framework for evaluation in learning from label proportions
J Hernández-González
Progress in Artificial Intelligence 8 (3), 359-373, 2019
2019
Crowd Learning with Candidate Labeling: An EM-Based Solution
I Benaran-Munoz, J Hernández-González, A Pérez
Conference of the Spanish Association for Artificial Intelligence, 13-23, 2018
2018
Candidate Labeling for Crowd Learning
I Beñaran-Muñoz, J Hernández-González, A Pérez
arXiv preprint arXiv:1804.10023, 2018
2018
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20