Juan José del Coz

Orcid: 0000-0002-4288-3839

According to our database1, Juan José del Coz authored at least 52 papers between 1999 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Matching Distributions Algorithms Based on the Earth Mover's Distance for Ordinal Quantification.
IEEE Trans. Neural Networks Learn. Syst., January, 2024

Quantification using Permutation-Invariant Networks based on Histograms.
CoRR, 2024

Kernel Density Estimation for Multiclass Quantification.
CoRR, 2024

2023
An Equivalence Analysis of Binary Quantification Methods.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Report on the 1st International Workshop on Learning to Quantify (LQ 2021).
SIGKDD Explor., 2022

UniOviedo(Team2) at LeQua 2022: Comparison of traditional quantifiers and a new method based on Energy Distance.
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.
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).
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.
Knowl. Inf. Syst., 2020

2019
Dynamic ensemble selection for quantification tasks.
Inf. Fusion, 2019

2018
Deep Learning and Preference Learning for Object Tracking: A Combined Approach.
Neural Process. Lett., 2018

2017
Why is quantification an interesting learning problem?
Prog. Artif. Intell., 2017

A family of admissible heuristics for A* to perform inference in probabilistic classifier chains.
Mach. Learn., 2017

A heuristic in A* for inference in nonlinear Probabilistic Classifier Chains.
Knowl. Based Syst., 2017

Using ensembles for problems with characterizable changes in data distribution: A case study on quantification.
Inf. Fusion, 2017

Deep learning to frame objects for visual target tracking.
Eng. Appl. Artif. Intell., 2017

A Review on Quantification Learning.
ACM Comput. Surv., 2017

2016
An overview of inference methods in probabilistic classifier chains for multilabel classification.
WIREs Data Mining Knowl. Discov., 2016

Analysis of clinical prognostic variables for Chronic Lymphocytic Leukemia decision-making problems.
J. Biomed. Informatics, 2016

Using tensor products to detect unconditional label dependence in multilabel classifications.
Inf. Sci., 2016

Combining Deep Learning and Preference Learning for Object Tracking.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

2015
Quantification-oriented learning based on reliable classifiers.
Pattern Recognit., 2015

Optimizing different loss functions in multilabel classifications.
Prog. Artif. Intell., 2015

Using A* for Inference in Probabilistic Classifier Chains.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014
Dependent binary relevance models for multi-label classification.
Pattern Recognit., 2014

2013
Multiclass Support Vector Machines With Example-Dependent Costs Applied to Plankton Biomass Estimation.
IEEE Trans. Neural Networks Learn. Syst., 2013

On the study of nearest neighbor algorithms for prevalence estimation in binary problems.
Pattern Recognit., 2013

Enhancing directed binary trees for multi-class classification.
Inf. Sci., 2013

Rectifying Classifier Chains for Multi-Label Classification.
Proceedings of the LWA 2013. Lernen, 2013

2012
Binary relevance efficacy for multilabel classification.
Prog. Artif. Intell., 2012

Learning data structure from classes: A case study applied to population genetics.
Inf. Sci., 2012

On the Problem of Error Propagation in Classifier Chains for Multi-label Classification.
Proceedings of the Data Analysis, Machine Learning and Knowledge Discovery, 2012

2011
Aggregating Independent and Dependent Models to Learn Multi-label Classifiers.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

2010
A semi-dependent decomposition approach to learn hierarchical classifiers.
Pattern Recognit., 2010

Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models.
J. Comput. Biol., 2010

Adapting Decision DAGs for Multipartite Ranking.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009
Learning Nondeterministic Classifiers.
J. Mach. Learn. Res., 2009

Soft Margin Trees.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Prediction and Inheritance of Phenotypes.
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.
Expert Syst. Appl., 2008

Learning to Predict One or More Ranks in Ordinal Regression Tasks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

2006
Learning the Reasons Why Groups of Consumers Prefer Some Food Products.
Proceedings of the Advances in Data Mining, 2006

2005
A Kernel Based Method for Discovering Market Segments in Beef Meat.
Proceedings of the Knowledge Discovery in Databases: PKDD 2005, 2005

2004
Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Feature subset selection for learning preferences: a case study.
Proceedings of the Machine Learning, 2004

Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection.
Proceedings of the Machine Learning: ECML 2004, 2004

Discovering Relevancies in Very Difficult Regression Problems: Applications to Sensory Data Analysis.
Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004

2002
Learning to Assess from Pair-Wise Comparisons.
Proceedings of the Advances in Artificial Intelligence, 2002

2000
Development of a distributive control scheme for fluorescent lighting based on LonWorks technology.
IEEE Trans. Ind. Electron., 2000

Un sistema inteligente para calificar morfológicamente a bovinos de la raza Asturiana de los Valles.
Inteligencia Artif., 2000

1999
Autonomous Clustering for Machine Learning.
Proceedings of the Foundations and Tools for Neural Modeling, 1999

Self-Organizing Cases to Find Paradigms.
Proceedings of the Foundations and Tools for Neural Modeling, 1999


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