Publicaciones (66) Publicaciones de JUAN JOSE DEL COZ VELASCO

2024

  1. 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

  2. QuantificationLib: A Python library for quantification and prevalence estimation

    SoftwareX, Vol. 26, pp. 101728

2023

  1. An Equivalence Analysis of Binary Quantification Methods

    Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023

2022

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

    CEUR Workshop Proceedings

2021

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

    International Conference on Information and Knowledge Management, Proceedings

2020

  1. Improving the ϵ -approximate algorithm for Probabilistic Classifier Chains

    Knowledge and Information Systems, Vol. 62, Núm. 7, pp. 2709-2738

2019

  1. Automatic plankton quantification using deep features

    Journal of Plankton Research, Vol. 41, Núm. 4, pp. 449-463

  2. Dynamic ensemble selection for quantification tasks

    Information Fusion, Vol. 45, pp. 1-15

2018

  1. Análisis de algoritmos de cuantificación basados en ajuste de distribuciones

    XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España

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

    Neural Processing Letters, Vol. 47, Núm. 3, pp. 859-876

2017

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

    Machine Learning, Vol. 106, Núm. 1, pp. 143-169

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

    Knowledge-Based Systems, Vol. 126, pp. 78-90

  3. A review onquantification learning

    ACM Computing Surveys, Vol. 50, Núm. 5

  4. Deep learning to frame objects for visual target tracking

    Engineering Applications of Artificial Intelligence, Vol. 65, pp. 406-420

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

    Information Fusion, Vol. 34, pp. 87-100

  6. Validation methods for plankton image classification systems

    Limnology and Oceanography: Methods, Vol. 15, Núm. 3, pp. 221-237

  7. Why is quantification an interesting learning problem?

    Progress in Artificial Intelligence, Vol. 6, Núm. 1, pp. 53-58

2016

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

    Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol. 6, Núm. 6, pp. 215-230

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

    Journal of Biomedical Informatics, Vol. 60, pp. 342-351

  3. Combining deep learning and preference learning for object tracking

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)