MANUEL
GÓMEZ OLMEDO
CATEDRÁTICO DE UNIVERSIDAD
ANDRÉS
CANO UTRERA
CATEDRÁTICO DE UNIVERSIDAD
Publications dans lesquelles il/elle collabore avec ANDRÉS CANO UTRERA (44)
2023
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Imprecise probabilistic models based on hierarchical intervals
Information Sciences, Vol. 638
2022
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Using Value-Based Potentials for Making Approximate Inference on Probabilistic Graphical Models
Mathematics, Vol. 10, Núm. 14
2021
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Computation of Kullback–Leibler divergence in Bayesian networks
Entropy, Vol. 23, Núm. 9
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Value-based potentials: Exploiting quantitative information regularity patterns in probabilistic graphical models
International Journal of Intelligent Systems, Vol. 36, Núm. 11, pp. 6913-6943
2020
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Learning sets of bayesian networks
Communications in Computer and Information Science
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MPE Computation in Bayesian Networks Using Mini-Bucket and Probability Trees Approximation
International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, Vol. 28, Núm. 5, pp. 785-805
2019
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A Bayesian approach to abrupt concept drift
Knowledge-Based Systems, Vol. 185
2018
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A linear programming based approach for evaluating interval-valued influence diagrams
XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España
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Virtual subconcept drift detection in discrete data using probabilistic graphical models
Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 17th International Conference, IPMU 2018, Cádiz, Spain, June 11-15, 2018, Proceedings, Part III
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Virtual subconcept drift detection in discrete data using probabilistic graphical models
Communications in Computer and Information Science
2017
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Estimating conditional probabilities by mixtures of low order conditional distributions
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Evaluating interval-valued influence diagrams
International Journal of Approximate Reasoning, Vol. 80, pp. 393-411
2016
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Improvements to Variable Elimination and Symbolic Probabilistic Inference for evaluating Influence Diagrams
International Journal of Approximate Reasoning, Vol. 70, pp. 13-35
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Using binary trees for the evaluation of influence diagrams
International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, Vol. 24, Núm. 1, pp. 59-89
2015
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An extended approach to learning recursive probability trees from data
International Journal of Intelligent Systems, Vol. 30, Núm. 3, pp. 355-383
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Máster en Ciencia de Datos e Ingeniería de Computadores: una apuesta por la formación especializada en el sector de las TIC
Enseñanza y aprendizaje de ingeniería de computadores: Revista de Experiencias Docentes en Ingeniería de Computadores, Núm. 5, pp. 5-16
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Variable elimination for interval-valued influence diagrams
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2014
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Extended probability trees for probabilistic graphical models
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8754, pp. 113-128
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On SPI for Evaluating Influence Diagrams
Communications in Computer and Information Science
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On SPI-Lazy evaluation of influence diagrams
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8754, pp. 97-112