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Pablo González-González
Pablo González-González
Centro de Inteligencia Artificial, University of Oviedo
Geverifieerd e-mailadres voor uniovi.es
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A review on quantification learning
P González-González, A Castaño, NV Chawla, JJD Coz
ACM Computing Surveys (CSUR) 50 (5), 74, 2017
144*2017
On the study of nearest neighbor algorithms for prevalence estimation in binary problems
J Barranquero, P González-González, J Díez, JJ Del Coz
Pattern Recognition 46 (2), 472-482, 2013
652013
Automatic plankton quantification using deep features
P González, A Castaño, EE Peacock, J Díez, JJ Del Coz, HM Sosik
Journal of Plankton Research 41 (4), 449-463, 2019
622019
Validation methods for plankton image classification systems
P González-González, E Álvarez, J Díez, Á López‐Urrutia, JJ del Coz
Limnology and Oceanography: Methods 15 (3), 221-237, 2017
592017
Why is quantification an interesting learning problem?
P González-González, J Díez, N Chawla, JJ del Coz
Progress in Artificial Intelligence 6 (1), 53-58, 2017
462017
Multiclass support vector machines with example-dependent costs applied to plankton biomass estimation
P González-González, E Álvarez, J Barranquero, J Díez, ...
IEEE transactions on neural networks and learning systems 24 (11), 1901-1905, 2013
262013
Learning to quantify: Methods and applications (LQ 2021)
JJ del Coz, P González, A Moreo, F Sebastiani
Proceedings of the 30th ACM International Conference on Information …, 2021
82021
An equivalence analysis of binary quantification methods
A Castaño, J Alonso, P González, JJ del Coz
Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 6944-6952, 2023
62023
Matching distributions algorithms based on the Earth mover’s distance for ordinal quantification
A Castaño, P González, JA González, JJ Del Coz
IEEE Transactions on Neural Networks and Learning Systems, 2022
62022
UniOviedo (Team1) at LeQua 2022: Sample-based quantification using deep learning.
P González
CLEF (Working Notes), 1881-1888, 2022
32022
Predicción taxonómica de muestras de microplancton usando técnicas de Aprendizaje Automático
P González-González, J Díez Peláez, JJ Coz Velasco
V Simposio de Teorıa y Aplicaciones de Minerıa de Datos (TAMIDA 2010), 2010
32010
Binary quantification and dataset shift: an experimental investigation
P González, A Moreo, F Sebastiani
Data Mining and Knowledge Discovery, 1-43, 2024
12024
Impact of multi‐output and stacking methods on feed efficiency prediction from genotype using machine learning algorithms
M Mora, P González, JR Quevedo, E Montañés, L Tusell, R Bergsma, ...
Journal of Animal Breeding and Genetics 140 (6), 638-652, 2023
12023
Histogram-based Deep Neural Network for Quantification.
P González, JJ del Coz
CIKM Workshops, 2021
12021
QuantificationLib: A Python library for quantification and prevalence estimation
A Castaño, J Alonso, P González, P Pérez, JJ del Coz
SoftwareX 26, 101728, 2024
2024
Quantification using Permutation-Invariant Networks based on Histograms
O Pérez-Mon, A Moreo, JJ del Coz, P González
arXiv preprint arXiv:2403.15123, 2024
2024
QuantificationLib: A Python library for quantification and prevalence estimation
A Castaño Gutiérrez, J Alonso González, P González González, ...
SoftwareX, 26, p. 101728 (2024); doi: 10.1016/j. softx. 2024.101728, 2024
2024
Kernel Density Estimation for Multiclass Quantification
A Moreo, P González, JJ del Coz
arXiv preprint arXiv:2401.00490, 2023
2023
Report on the 1st International Workshop on Learning to Quantify (LQ 2021)
JJ del Coz, P González, A Moreo, F Sebastiani
ACM SIGKDD Explorations Newsletter 24 (1), 49-51, 2022
2022
UniOviedo (Team1) at LeQua 2022: Sample-based quantification using deep learning
P González González
Ceur workshop proceedings, 2022
2022
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Artikelen 1–20