Juan José del Coz

57 papers A* 4A 2Journal 35Unranked 16
YearRankTypeTitle / Venue / Authors
2026 J jnl
Quantification via gaussian latent space representations.
Neural Networks
Olaya Pérez-Mon, Juan José del Coz, Pablo González
2025 J jnl
Kernel density estimation for multiclass quantification.
Mach. Learn.
Alejandro Moreo, Pablo González, Juan José del Coz
2025 J jnl
Quantification using permutation-invariant networks based on histograms.
Neural Comput. Appl.
Olaya Pérez-Mon, Alejandro Moreo, Juan José del Coz, Pablo González
2025 J jnl
Quantification via Gaussian Latent Space Representations.
CoRR
Olaya Pérez-Mon, Juan José del Coz, Pablo González
2024 J jnl
Kernel Density Estimation for Multiclass Quantification.
CoRR
Alejandro Moreo, Pablo González, Juan José del Coz
2024 J jnl
Matching Distributions Algorithms Based on the Earth Mover's Distance for Ordinal Quantification.
IEEE Trans. Neural Networks Learn. Syst.
Alberto Castaño, Pablo González, Jaime Alonso González, Juan José del Coz
2024 J jnl
Quantification using Permutation-Invariant Networks based on Histograms.
CoRR
Olaya Pérez-Mon, Alejandro Moreo, Juan José del Coz, Pablo González
2024 J jnl
QuantificationLib: A Python library for quantification and prevalence estimation.
SoftwareX
Alberto Castaño, Jaime Alonso, Pablo González, Pablo Pérez, Juan José del Coz
2023 A* conf
An Equivalence Analysis of Binary Quantification Methods.
AAAI
Alberto Castaño, Jaime Alonso, Pablo González, Juan José del Coz
2022 J jnl
Report on the 1st International Workshop on Learning to Quantify (LQ 2021).
SIGKDD Explor.
Juan José del Coz, Pablo González, Alejandro Moreo, Fabrizio Sebastiani
2022 — conf
UniOviedo(Team2) at LeQua 2022: Comparison of traditional quantifiers and a new method based on Energy Distance.
CLEF (Working Notes)
Juan José del Coz
2021 — conf
Histogram-based Deep Neural Network for Quantification.
CIKM Workshops
Pablo González, Juan José del Coz
2021 A conf
Learning to Quantify: Methods and Applications (LQ 2021).
CIKM
Juan José del Coz, Pablo González, Alejandro Moreo, Fabrizio Sebastiani
2020 J jnl
Improving the ε-approximate algorithm for Probabilistic Classifier Chains.
Knowl. Inf. Syst.
Miriam Fdez-Díaz, Laura Fdez-Díaz, Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz
2019 J jnl
Dynamic ensemble selection for quantification tasks.
Inf. Fusion
Pablo Pérez-Gállego, Alberto Castaño, José Ramón Quevedo, Juan José del Coz
2019 J jnl
Rectifying Classifier Chains for Multi-Label Classification.
CoRR
Robin Senge, Juan José del Coz, Eyke Hüllermeier
2018 J jnl
Deep Learning and Preference Learning for Object Tracking: A Combined Approach.
Neural Process. Lett.
Shu-Chao Pang, Juan José del Coz, Zhezhou Yu, Oscar Luaces, Jorge Díez
2017 J jnl
A Review on Quantification Learning.
ACM Comput. Surv.
Pablo González, Alberto Castaño, Nitesh V. Chawla, Juan José del Coz
2017 J jnl
A family of admissible heuristics for A* to perform inference in probabilistic classifier chains.
Mach. Learn.
Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz
2017 J jnl
A heuristic in A* for inference in nonlinear Probabilistic Classifier Chains.
Knowl. Based Syst.
Deiner Mena, José Ramón Quevedo, Elena Montañés, Juan José del Coz
2017 J jnl
Deep learning to frame objects for visual target tracking.
Eng. Appl. Artif. Intell.
Shu-Chao Pang, Juan José del Coz, Zhezhou Yu, Oscar Luaces, Jorge Díez
2017 J jnl
Using ensembles for problems with characterizable changes in data distribution: A case study on quantification.
Inf. Fusion
Pablo Pérez-Gállego, José Ramón Quevedo, Juan José del Coz
2017 J jnl
Why is quantification an interesting learning problem?
Prog. Artif. Intell.
Pablo González, Jorge Díez, Nitesh V. Chawla, Juan José del Coz
2016 J jnl
An overview of inference methods in probabilistic classifier chains for multilabel classification.
WIREs Data Mining Knowl. Discov.
Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz
2016 J jnl
Analysis of clinical prognostic variables for Chronic Lymphocytic Leukemia decision-making problems.
J. Biomed. Informatics
Enrique J. deAndrés-Galiana, Juan Luis Fernández Martínez, Oscar Luaces, Juan José del Coz, Leticia Huergo-Zapico, Andrea Acebes-Huerta, Segundo González, Ana P. González-Rodríguez
2016 — conf
Combining Deep Learning and Preference Learning for Object Tracking.
ICONIP (3)
Shu-Chao Pang, Juan José del Coz, Zhezhou Yu, Oscar Luaces, Jorge Díez
2016 J jnl
Using tensor products to detect unconditional label dependence in multilabel classifications.
Inf. Sci.
Jorge Díez, Juan José del Coz, Oscar Luaces, Antonio Bahamonde
2015 J jnl
Optimizing different loss functions in multilabel classifications.
Prog. Artif. Intell.
Jorge Díez, Oscar Luaces, Juan José del Coz, Antonio Bahamonde
2015 J jnl
Quantification-oriented learning based on reliable classifiers.
Pattern Recognit.
José Barranquero, Jorge Díez, Juan José del Coz
2015 A* conf
Using A* for Inference in Probabilistic Classifier Chains.
IJCAI
Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz
2014 J jnl
Dependent binary relevance models for multi-label classification.
Pattern Recognit.
Elena Montañés, Robin Senge, José Barranquero, José Ramón Quevedo, Juan José del Coz, Eyke Hüllermeier
2013 J jnl
Enhancing directed binary trees for multi-class classification.
Inf. Sci.
Elena Montañés, José Barranquero, Jorge Díez, Juan José del Coz
2013 J jnl
Multiclass Support Vector Machines With Example-Dependent Costs Applied to Plankton Biomass Estimation.
IEEE Trans. Neural Networks Learn. Syst.
Pablo González, Eva Alvarez, José Barranquero, Jorge Díez, Rafael Gonzalez-Quiros, Enrique Nogueira, Angel Lopez-Urrutia, Juan José del Coz
2013 J jnl
On the study of nearest neighbor algorithms for prevalence estimation in binary problems.
Pattern Recognit.
José Barranquero, Pablo González, Jorge Díez, Juan José del Coz
2013 — conf
Rectifying Classifier Chains for Multi-Label Classification.
LWA
Robin Senge, Juan José del Coz, Eyke Hüllermeier
2012 J jnl
Binary relevance efficacy for multilabel classification.
Prog. Artif. Intell.
Oscar Luaces, Jorge Díez, José Barranquero, Juan José del Coz, Antonio Bahamonde
2012 J jnl
Learning data structure from classes: A case study applied to population genetics.
Inf. Sci.
Juan José del Coz, Jorge Díez, Antonio Bahamonde, Félix Goyache
2012 — conf
On the Problem of Error Propagation in Classifier Chains for Multi-label Classification.
GfKl
Robin Senge, Juan José del Coz, Eyke Hüllermeier
2011 — conf
Aggregating Independent and Dependent Models to Learn Multi-label Classifiers.
ECML/PKDD (2)
Elena Montañés, José Ramón Quevedo, Juan José del Coz
2010 J jnl
A semi-dependent decomposition approach to learn hierarchical classifiers.
Pattern Recognit.
Jorge Díez, Juan José del Coz, Antonio Bahamonde
2010 — conf
Adapting Decision DAGs for Multipartite Ranking.
ECML/PKDD (3)
José Ramón Quevedo, Elena Montañés, Oscar Luaces, Juan José del Coz
2010 J jnl
Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models.
J. Comput. Biol.
Oscar Luaces, José Ramón Quevedo, Miguel Pérez-Enciso, Jorge Díez, Juan José del Coz, Antonio Bahamonde
2009 J jnl
Learning Nondeterministic Classifiers.
J. Mach. Learn. Res.
Juan José del Coz, Jorge Díez, Antonio Bahamonde
2009 — conf
Prediction and Inheritance of Phenotypes.
IWINAC (1)
Antonio Bahamonde, Jaime Alonso, Juan José del Coz, Jorge Díez, José Ramón Quevedo, Oscar Luaces
2009 — conf
Soft Margin Trees.
ECML/PKDD (1)
Jorge Díez, Juan José del Coz, Antonio Bahamonde, Oscar Luaces
2008 J jnl
Clustering people according to their preference criteria.
Expert Syst. Appl.
Jorge Díez, Juan José del Coz, Oscar Luaces, Antonio Bahamonde
2008 — conf
Learning to Predict One or More Ranks in Ordinal Regression Tasks.
ECML/PKDD (1)
Jaime Alonso, Juan José del Coz, Jorge Díez, Oscar Luaces, Antonio Bahamonde
2006 A* conf
Learning the Reasons Why Groups of Consumers Prefer Some Food Products.
ICDM
Juan José del Coz, Jorge Díez, Antonio Bahamonde, Carlos Sañudo, Matilde Alfonso, Philippe Berge, Eric Dransfield, Costas Stamataris, Demetrios Zygoyiannis, Tyri Valdimarsdottir, Edi Piasentier, Geoffrey Nute, Alan Fisher
2005 — conf
A Kernel Based Method for Discovering Market Segments in Beef Meat.
PKDD
Jorge Díez, Juan José del Coz, Carlos Sañudo, Pere Albertí, Antonio Bahamonde
2004 — conf
Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection.
ECML
Oscar Luaces, Gustavo F. Bayón, José Ramón Quevedo, Jorge Díez, Juan José del Coz, Antonio Bahamonde
2004 A conf
Discovering Relevancies in Very Difficult Regression Problems: Applications to Sensory Data Analysis.
ECAI
Jorge Díez, Gustavo F. Bayón, José Ramón Quevedo, Juan José del Coz, Oscar Luaces, Jaime Alonso, Antonio Bahamonde
2004 A* conf
Feature subset selection for learning preferences: a case study.
ICML
Antonio Bahamonde, Gustavo F. Bayón, Jorge Díez, José Ramón Quevedo, Oscar Luaces, Juan José del Coz, Jaime Alonso, Félix Goyache
2004 — conf
Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM.
NIPS
Juan José del Coz, Gustavo F. Bayón, Jorge Díez, Oscar Luaces, Antonio Bahamonde, Carlos Sañudo
2002 — conf
Learning to Assess from Pair-Wise Comparisons.
IBERAMIA
Jorge Díez, Juan José del Coz, Oscar Luaces, Félix Goyache, Jaime Alonso, A. M. Peña, Antonio Bahamonde
2000 J jnl
Un sistema inteligente para calificar morfológicamente a bovinos de la raza Asturiana de los Valles.
Inteligencia Artif.
F. López, Félix Goyache, José Ramón Quevedo, Jaime Alonso, José Ranilla, Oscar Luaces, Antonio Bahamonde, Juan José del Coz
1999 — conf
Autonomous Clustering for Machine Learning.
IWANN (1)
Oscar Luaces, Juan José del Coz, José Ramón Quevedo, Jaime Alonso, José Ranilla, Antonio Bahamonde
1999 — conf
Self-Organizing Cases to Find Paradigms.
IWANN (1)
Juan José del Coz, Oscar Luaces, José Ramón Quevedo, Jaime Alonso, José Ranilla, Antonio Bahamonde