Jerónimo Hernández González

Jerónimo Hernández González

Lecturer Professor

Scopus Author ID: 55753089000
Researcher ID: AAC-8158-2020
Knowledge area: Llenguatges i Sistemes Informàtics

Contact Information
Department of Mathematics and Computer Science
Facultat de Matemàtiques i Informàtica, despatx E1 01 Gran Via de les Corts Catalanes, 585
+34 93 402 1635
jeronimo.hernandez(a)ub.edu

Teaching imparted

Models Gràfics Probabilístics (University Master's Degree) - Inteligencia Artificial - Universidad de Barcelona.
Models Gràfics Probabilístics (University Master's Degree) - Fonaments de la Ciència de Dades - Universidad de Barcelona.
Métodos supervisados (University Master's Degree) - Master degree in Artificial Intelligence Research - Universidad Internacional Menéndez Pelayo.
Minería de Datos (Bachelor's degree) - Degree on Computer Science - Universidad del País Vasco/Euskal Herriko Unibertsitatea.
Minería de datos: fundamentos y aplicaciones empresariales y bioinformáticas (University Master's Degree) - Ingeniería Computacional y Sistemas Inteligentes - Universidad del País Vasco/Euskal Herriko Unibertsitatea.
Exploración y análisis de datos (University Master's Degree) - Ingeniería Computacional y Sistemas Inteligentes - Universidad del País Vasco/Euskal Herriko Unibertsitatea.
Diagnosis Decision Support Systems (Bachelor's degree) - Degree on Biomedical Engineering - Universidad de Vic.
Aprendizaje no supervisado (Máster no oficial) - Master degree in Artificial Intelligence - Universitat Internacional Valenciana.
Treball final de màster (University Master's Degree) - Master degree in Data Science - Universidad Oberta de Catalunya.

Stays abroad in Research Centers

Institut d'Investigació en Intel·ligència Artificial (IIIA-CSIC). Bellaterra. SPAIN. 2018 (1 Years) . Probabilistic graphical models . Postdoctoral
Marchine learning department, Carnegie Mellon University. Pittsburgh. UNITED STATES. 2016 (5 Months) . Analysis of knowledge databases . Postdoctoral - PA
National Key Laboratory for Novel Software Technology, Nanjing University. Nanjing. CHINA. 2014 (3 Months) . Weakly supervised learning . Ph.D. Student

Journal Publications

Hernández-González, J.; Inza, I.; Lozano, J.A. (2015). Weak supervision and other non-standard classification problems: a taxonomy. Pattern Recognition Letters, 69, pp. 49 - 55 . https://doi.org/10.1016/j.patrec.2015.10.008 . ISSN: 0167-8655
Hernández-González, J.; Inza, I.; Lozano, J.A. (2013). Learning Bayesian network classifiers from label proportions. Pattern Recognition, 46, pp. 3425 - 3440 . https://doi.org/10.1016/j.patcog.2013.05.002 . ISSN: 0031-3203
Hernández-González, J.; Inza, I.; Lozano, J.A. (2015). Multidimensional learning from crowds: usefulness and application of expertise detection. International Journal of Intelligent Systems, 30, pp. 326 - 354 . https://doi.org/10.1002/int.21702 . ISSN: 0884-8173
Hernández-González, J; Rodriguez, D.; Inza, I., Harrison, R.; Lozano, J.A. (2017). Learning to classify software defects from crowds: a novel approach. Applied Soft Computing, 62, pp. 579 - 591 . https://doi.org/10.1016/j.asoc.2017.10.047 . ISSN: 1568-4946
Hernández-González, J.; Inza, I.; Granado, I.; Basurko, O.C.; Fernandes, J.A.; Lozano, J.A. (2019). Aggregated outputs by linear models: an application on marine litter beaching prediction. Information Sciences, 481, pp. 381 - 393 . https://doi.org/10.1016/j.ins.2018.12.083 . ISSN: 0020-0255
Hernández-González, J.; Inza, I.; Lozano, J.A. (2018). A note on the behavior of majority voting in multi-class domains with biased annotators. IEEE Transactions on Knowledge and Data Engineering, 31(1), pp. 195 - 200 . https://doi.org/10.1109/TKDE.2018.2845400 . ISSN: 1041-4347
Granado, I.; Basurko, O.C.; Rubio, A.; Ferrer, L.; Hernández-González, J.; Epelde, I.; Fernandes, J.A. (2019). Beach litter forecasting on the south-eastern coast of the Bay of Biscay: a bayesian networks approach. Continental Shelf Research, 180, pp. 14 - 23 . https://doi.org/10.1016/j.csr.2019.04.016 . ISSN: 0278-4343
Hernández-González, J. (2019). A framework for evaluation in learning from label proportions. Progress in Artificial Intelligence, 8, pp. 359 - 373 . https://doi.org/10.1007/s13748-019-00187-x . ISSN: 2192-6352
Hernández-González, J.; Inza, I.; Crisol-Ortíz, L.; Guembe, M.A.; Iñarra, M.J.; Lozano, J.A. (2016). Fitting the data from embryo implantation prediction: learning from label proportions. Statistical Methods in Medical Research, 27(4), pp. 1056 - 1066 . https://doi.org/10.1177/0962280216651098 . ISSN: 0962-2802
Hernández-González, J.; Rodriguez, D.; Inza, I.; Harrison, R.; Lozano, J.A. (2018). Two datasets of defect reports labeled by a crowd of annotators of unknown reliability. Data in Brief, 18, pp. 840 - 845 . Institutional Repository . ISSN: 2352-3409