PABLO
GONZALEZ GONZALEZ
Profesor Ayudante Doctor
Publications (15) PABLO GONZALEZ GONZALEZ publications View referenced research data.
2024
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Binary quantification and dataset shift: an experimental investigation
Data Mining and Knowledge Discovery, Vol. 38, Núm. 4, pp. 1670-1712
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Importance of the inclusion of self-assessment tools in theoretical multimedia contents
EDULEARN24 Proceedings
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Matching Distributions Algorithms Based on the Earth Mover's Distance for Ordinal Quantification
IEEE Transactions on Neural Networks and Learning Systems, Vol. 35, Núm. 1, pp. 1050-1061
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QuantificationLib: A Python library for quantification and prevalence estimation
SoftwareX, Vol. 26, pp. 101728
2023
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An Equivalence Analysis of Binary Quantification Methods
Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023
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An Equivalence Analysis of Binary Quantification Methods
THIRTY-SEVENTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 37 NO 6
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Impact of multi-output and stacking methods on feed efficiency prediction from genotype using machine learning algorithms
Journal of Animal Breeding and Genetics, Vol. 140, Núm. 6, pp. 638-652
2022
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UniOviedo(Team1) at LeQua 2022: Sample-based quantification using deep learning
CEUR Workshop Proceedings
2021
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Learning to Quantify: Methods and Applications (LQ 2021)
International Conference on Information and Knowledge Management, Proceedings
2019
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Automatic plankton quantification using deep features
Journal of Plankton Research, Vol. 41, Núm. 4, pp. 449-463
2017
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A review onquantification learning
ACM Computing Surveys, Vol. 50, Núm. 5
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Validation methods for plankton image classification systems
Limnology and Oceanography: Methods, Vol. 15, Núm. 3, pp. 221-237
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Why is quantification an interesting learning problem?
Progress in Artificial Intelligence, Vol. 6, Núm. 1, pp. 53-58
2013
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Multiclass support vector machines with example-dependent costs applied to plankton biomass estimation
IEEE Transactions on Neural Networks and Learning Systems, Vol. 24, Núm. 11, pp. 1901-1905
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On the study of nearest neighbor algorithms for prevalence estimation in binary problems
Pattern Recognition, Vol. 46, Núm. 2, pp. 472-482