Juan José del Coz

According to our database, Juan José del Coz authored at least 53 papers between 1999 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Matching Distributions Algorithms Based on the Earth Mover's Distance for Ordinal Quantification.

Alberto Castaño, Pablo González, Jaime Alonso González, Juan José del Coz

IEEE Trans. Neural Networks Learn. Syst., January, 2024

QuantificationLib: A Python library for quantification and prevalence estimation.

Alberto Castaño, Jaime Alonso, Pablo González, Pablo Pérez, Juan José del Coz

SoftwareX, 2024

Quantification using Permutation-Invariant Networks based on Histograms.

Olaya Pérez-Mon, Alejandro Moreo, Juan José del Coz, Pablo González

CoRR, 2024

Kernel Density Estimation for Multiclass Quantification.

Alejandro Moreo, Pablo González, Juan José del Coz

CoRR, 2024

2023

An Equivalence Analysis of Binary Quantification Methods.

Alberto Castaño, Jaime Alonso, Pablo González, Juan José del Coz

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Report on the 1st International Workshop on Learning to Quantify (LQ 2021).

Juan José del Coz, Pablo González, Alejandro Moreo, Fabrizio Sebastiani

SIGKDD Explor., 2022

UniOviedo(Team2) at LeQua 2022: Comparison of traditional quantifiers and a new method based on Energy Distance.

Juan José del Coz

Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum, Bologna, Italy, September 5th - to, 2022

2021

Histogram-based Deep Neural Network for Quantification.

Pablo González, Juan José del Coz

Proceedings of the CIKM 2021 Workshops co-located with 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), 2021

Learning to Quantify: Methods and Applications (LQ 2021).

Juan José del Coz, Pablo González, Alejandro Moreo, Fabrizio Sebastiani

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Improving the ε-approximate algorithm for Probabilistic Classifier Chains.

Miriam Fdez-Díaz, Laura Fdez-Díaz, Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz

Knowl. Inf. Syst., 2020

2019

Dynamic ensemble selection for quantification tasks.

Pablo Pérez-Gállego, Alberto Castaño, José Ramón Quevedo, Juan José del Coz

Inf. Fusion, 2019

2018

Deep Learning and Preference Learning for Object Tracking: A Combined Approach.

Shu-Chao Pang, Juan José del Coz, Zhezhou Yu, Oscar Luaces, Jorge Díez

Neural Process. Lett., 2018

2017

Why is quantification an interesting learning problem?

Pablo González, Jorge Díez, Nitesh V. Chawla, Juan José del Coz

Prog. Artif. Intell., 2017

A family of admissible heuristics for A* to perform inference in probabilistic classifier chains.

Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz

Mach. Learn., 2017

A heuristic in A* for inference in nonlinear Probabilistic Classifier Chains.

Deiner Mena, José Ramón Quevedo, Elena Montañés, Juan José del Coz

Knowl. Based Syst., 2017

Using ensembles for problems with characterizable changes in data distribution: A case study on quantification.

Pablo Pérez-Gállego, José Ramón Quevedo, Juan José del Coz

Inf. Fusion, 2017

Deep learning to frame objects for visual target tracking.

Shu-Chao Pang, Juan José del Coz, Zhezhou Yu, Oscar Luaces, Jorge Díez

Eng. Appl. Artif. Intell., 2017

A Review on Quantification Learning.

Pablo González, Alberto Castaño, Nitesh V. Chawla, Juan José del Coz

ACM Comput. Surv., 2017

2016

An overview of inference methods in probabilistic classifier chains for multilabel classification.

Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz

WIREs Data Mining Knowl. Discov., 2016

Analysis of clinical prognostic variables for Chronic Lymphocytic Leukemia decision-making problems.

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

J. Biomed. Informatics, 2016

Using tensor products to detect unconditional label dependence in multilabel classifications.

Jorge Díez, Juan José del Coz, Oscar Luaces, Antonio Bahamonde

Inf. Sci., 2016

Combining Deep Learning and Preference Learning for Object Tracking.

Shu-Chao Pang, Juan José del Coz, Zhezhou Yu, Oscar Luaces, Jorge Díez

Proceedings of the Neural Information Processing - 23rd International Conference, 2016

2015

Quantification-oriented learning based on reliable classifiers.

José Barranquero, Jorge Díez, Juan José del Coz

Pattern Recognit., 2015

Optimizing different loss functions in multilabel classifications.

Jorge Díez, Oscar Luaces, Juan José del Coz, Antonio Bahamonde

Prog. Artif. Intell., 2015

Using A* for Inference in Probabilistic Classifier Chains.

Deiner Mena, Elena Montañés, José Ramón Quevedo, Juan José del Coz

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Dependent binary relevance models for multi-label classification.

Elena Montañés, Robin Senge, José Barranquero, José Ramón Quevedo, Juan José del Coz, Eyke Hüllermeier

Pattern Recognit., 2014

2013

Multiclass Support Vector Machines With Example-Dependent Costs Applied to Plankton Biomass Estimation.

Pablo González, Eva Alvarez, José Barranquero, Jorge Díez, Rafael Gonzalez-Quiros, Enrique Nogueira, Angel Lopez-Urrutia, Juan José del Coz

IEEE Trans. Neural Networks Learn. Syst., 2013

On the study of nearest neighbor algorithms for prevalence estimation in binary problems.

José Barranquero, Pablo González, Jorge Díez, Juan José del Coz

Pattern Recognit., 2013

Enhancing directed binary trees for multi-class classification.

Elena Montañés, José Barranquero, Jorge Díez, Juan José del Coz

Inf. Sci., 2013

Rectifying Classifier Chains for Multi-Label Classification.

Robin Senge, Juan José del Coz, Eyke Hüllermeier

Proceedings of the LWA 2013. Lernen, 2013

2012

Binary relevance efficacy for multilabel classification.

Oscar Luaces, Jorge Díez, José Barranquero, Juan José del Coz, Antonio Bahamonde

Prog. Artif. Intell., 2012

Learning data structure from classes: A case study applied to population genetics.

Juan José del Coz, Jorge Díez, Antonio Bahamonde, Félix Goyache

Inf. Sci., 2012

On the Problem of Error Propagation in Classifier Chains for Multi-label Classification.

Robin Senge, Juan José del Coz, Eyke Hüllermeier

Proceedings of the Data Analysis, Machine Learning and Knowledge Discovery, 2012

2011

Aggregating Independent and Dependent Models to Learn Multi-label Classifiers.

Elena Montañés, José Ramón Quevedo, Juan José del Coz

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

2010

A semi-dependent decomposition approach to learn hierarchical classifiers.

Jorge Díez, Juan José del Coz, Antonio Bahamonde

Pattern Recognit., 2010

Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models.

Oscar Luaces, José Ramón Quevedo, Miguel Pérez-Enciso, Jorge Díez, Juan José del Coz, Antonio Bahamonde

J. Comput. Biol., 2010

Adapting Decision DAGs for Multipartite Ranking.

José Ramón Quevedo, Elena Montañés, Oscar Luaces, Juan José del Coz

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009

Learning Nondeterministic Classifiers.

Juan José del Coz, Jorge Díez, Antonio Bahamonde

J. Mach. Learn. Res., 2009

Soft Margin Trees.

Jorge Díez, Juan José del Coz, Antonio Bahamonde, Oscar Luaces

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Prediction and Inheritance of Phenotypes.

Antonio Bahamonde, Jaime Alonso, Juan José del Coz, Jorge Díez, José Ramón Quevedo, Oscar Luaces

Proceedings of the Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira.s Scientific Legacy, 2009

2008

Clustering people according to their preference criteria.

Jorge Díez, Juan José del Coz, Oscar Luaces, Antonio Bahamonde

Expert Syst. Appl., 2008

Learning to Predict One or More Ranks in Ordinal Regression Tasks.

Jaime Alonso, Juan José del Coz, Jorge Díez, Oscar Luaces, Antonio Bahamonde

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

2006

Learning the Reasons Why Groups of Consumers Prefer Some Food Products.

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

Proceedings of the Advances in Data Mining, 2006

2005

A Kernel Based Method for Discovering Market Segments in Beef Meat.

Jorge Díez, Juan José del Coz, Carlos Sañudo, Pere Albertí, Antonio Bahamonde

Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

2004

Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM.

Juan José del Coz, Gustavo F. Bayón, Jorge Díez, Oscar Luaces, Antonio Bahamonde, Carlos Sañudo

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Feature subset selection for learning preferences: a case study.

Antonio Bahamonde, Gustavo F. Bayón, Jorge Díez, José Ramón Quevedo, Oscar Luaces, Juan José del Coz, Jaime Alonso, Félix Goyache

Proceedings of the Machine Learning, 2004

Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection.

Oscar Luaces, Gustavo F. Bayón, José Ramón Quevedo, Jorge Díez, Juan José del Coz, Antonio Bahamonde

Proceedings of the Machine Learning: ECML 2004, 2004

Discovering Relevancies in Very Difficult Regression Problems: Applications to Sensory Data Analysis.

Jorge Díez, Gustavo F. Bayón, José Ramón Quevedo, Juan José del Coz, Oscar Luaces, Jaime Alonso, Antonio Bahamonde

Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004

2002

Learning to Assess from Pair-Wise Comparisons.

Jorge Díez, Juan José del Coz, Oscar Luaces, Félix Goyache, Jaime Alonso, A. M. Peña, Antonio Bahamonde

Proceedings of the Advances in Artificial Intelligence, 2002

2000

Development of a distributive control scheme for fluorescent lighting based on LonWorks technology.

José Marcos Alonso Alvarez, Javier Ribas Bueno, Juan José del Coz Velasco, Antonio Javier Calleja Rodriguez, Emilio López Corominas, Manuel Rico-Secades

IEEE Trans. Ind. Electron., 2000

Un sistema inteligente para calificar morfológicamente a bovinos de la raza Asturiana de los Valles.

F. López, Félix Goyache, José Ramón Quevedo, Jaime Alonso, José Ranilla, Oscar Luaces, Antonio Bahamonde, Juan José del Coz

Inteligencia Artif., 2000

1999

Autonomous Clustering for Machine Learning.

Oscar Luaces, Juan José del Coz, José Ramón Quevedo, Jaime Alonso, José Ranilla, Antonio Bahamonde

Proceedings of the Foundations and Tools for Neural Modeling, 1999

Self-Organizing Cases to Find Paradigms.

Juan José del Coz, Oscar Luaces, José Ramón Quevedo, Jaime Alonso, José Ranilla, Antonio Bahamonde

Proceedings of the Foundations and Tools for Neural Modeling, 1999