Jerónimo Hernández-González

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 21

Top Topics

Learning To Classify

Weakly Supervised

Top Venues

Int. J. Intell. Syst.

Publications

Anna Cascarano, Jordi Mur-Petit, Jerónimo Hernández-González, Marina Camacho, Nina de Toro Eadie, Polyxeni Gkontra, Marc Chadeau-Hyam, Jordi Vitrià, Karim Lekadir
Machine and deep learning for longitudinal biomedical data: a review of methods and applications. Artif. Intell. Rev. 56 (S2) (2023)
Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez
On the use of the descriptive variable for enhancing the aggregation of crowdsourced labels. Knowl. Inf. Syst. 65 (1) (2023)
Jerónimo Hernández-González, Pedro Javier Herrera
On the Supervision of Peer Assessment Tasks: An Efficient Instructor Guidance Technique. IEEE Trans. Learn. Technol. 16 (6) (2023)
Vien Ngoc Dang, Adrià Casamitjana, Martijn P. A. Starmans, Carlos Martín-Isla, Jerónimo Hernández-González, Karim Lekadir, Alzheimer's Disease Neuroimaging Initiative
Auditing Unfair Biases in CNN-Based Diagnosis of Alzheimer's Disease. CLIP/FAIMI/EPIMI@MICCAI (2023)
Jerónimo Hernández-González, Aritz Pérez
On the relative value of weak information of supervision for learning generative models: An empirical study. Int. J. Approx. Reason. 150 (2022)
Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez
Machine Learning From Crowds Using Candidate Set-Based Labeling. IEEE Intell. Syst. 37 (6) (2022)
Jerónimo Hernández-González, Olga Valls, Adrián Torres-Martín, Jesús Cerquides
Modeling three sources of uncertainty in assisted reproductive technologies with probabilistic graphical models. Comput. Biol. Medicine 150 (2022)
Vien Ngoc Dang, Anna Cascarano, Rosa H. Mulder, Charlotte Cecil, Maria A. Zuluaga, Jerónimo Hernández-González, Karim Lekadir
Fairness and bias correction in machine learning for depression prediction: results from four different study populations. CoRR (2022)
Adrián Torres-Martín, Jerónimo Hernández-González, Jesús Cerquides
Validation on Real Data of an Extended Embryo-Uterine Probabilistic Graphical Model for Embryo Selection. CCIA (2021)
Jerónimo Hernández-González, Jesús Cerquides
A Robust Solution to Variational Importance Sampling of Minimum Variance. Entropy 22 (12) (2020)
Jerónimo Hernández-González, Iñaki Inza, Igor Granado, Oihane C. Basurko, Jose A. Fernandes, José Antonio Lozano
Aggregated outputs by linear models: An application on marine litter beaching prediction. Inf. Sci. 481 (2019)
Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano
A Note on the Behavior of Majority Voting in Multi-Class Domains with Biased Annotators. IEEE Trans. Knowl. Data Eng. 31 (1) (2019)
Jerónimo Hernández-González, Joan Capdevila, Jesús Cerquides
Variational Importance Sampling: Initial Findings. CCIA (2019)
Jerónimo Hernández-González
A framework for evaluation in learning from label proportions. Prog. Artif. Intell. 8 (3) (2019)
Jerónimo Hernández-González, Daniel Rodríguez, Iñaki Inza, Rachel Harrison, José Antonio Lozano
Learning to classify software defects from crowds: A novel approach. Appl. Soft Comput. 62 (2018)
Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez
Crowd Learning with Candidate Labeling: An EM-Based Solution. CAEPIA (2018)
Iker Beñaran-Muñoz, Jerónimo Hernández-González, Aritz Pérez
Weak Labeling for Crowd Learning. CoRR (2018)
Jerónimo Hernández-González
Evaluation in Learning from Label Proportions: An Approximation to the Precision-Recall Curve. CAEPIA (2018)
Jerónimo Hernández-González, Estevam R. Hruschka Jr., Tom M. Mitchell
Merging knowledge bases in different languages. TextGraphs@ACL (2017)
Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano
Learning from Proportions of Positive and Unlabeled Examples. Int. J. Intell. Syst. 32 (2) (2017)
Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano
Weak supervision and other non-standard classification problems: A taxonomy. Pattern Recognit. Lett. 69 (2016)
Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano
Multidimensional Learning from Crowds: Usefulness and Application of Expertise Detection. Int. J. Intell. Syst. 30 (3) (2015)
Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano
A Novel Weakly Supervised Problem: Learning from Positive-Unlabeled Proportions. CAEPIA (2015)
Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano
Learning from Crowds in Multi-dimensional Classification Domains. CAEPIA (2013)
Jerónimo Hernández-González, Iñaki Inza, José Antonio Lozano
Learning Bayesian network classifiers from label proportions. Pattern Recognit. 46 (12) (2013)
Jerónimo Hernández-González, Iñaki Inza
Learning Naive Bayes Models for Multiple-Instance Learning with Label Proportions. CAEPIA (2011)