Verónica
Bolón Canedo
Profesora Titular de Universidad
María Amparo
Alonso Betanzos
Catedrática de Universidad
Publicaciones en las que colabora con María Amparo Alonso Betanzos (116)
2024
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A review of green artificial intelligence: Towards a more sustainable future
Neurocomputing, Vol. 599
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Preface
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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The imbalance problem: A comparison of sampling approaches using different parameters and feature selection methods in the context of classification
Expert Systems, Vol. 41, Núm. 8
2023
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Data-driven predictive maintenance framework for railway systems
Intelligent Data Analysis, Vol. 27, Núm. 4, pp. 1087-1102
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E2E-FS: An End-to-End Feature Selection Method for Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 45, Núm. 7, pp. 8311-8323
2022
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A TripAdvisor Dataset for Dyadic Context Analysis
Zenodo
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A TripAdvisor Dataset for Dyadic Context Analysis
Zenodo
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Anomaly Detection on Natural Language Processing to Improve Predictions on Tourist Preferences
Electronics (Switzerland), Vol. 11, Núm. 5
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Fast anomaly detection with locality-sensitive hashing and hyperparameter autotuning
Information Sciences, Vol. 607, pp. 1245-1264
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Feature Selection: From the Past to the Future
Learning and Analytics in Intelligent Systems (Springer Nature), pp. 11-34
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How important is data quality? Best classifiers vs best features
Neurocomputing, Vol. 470, pp. 365-375
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Low-precision feature selection on microarray data: an information theoretic approach
Medical and Biological Engineering and Computing, Vol. 60, Núm. 5, pp. 1333-1345
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Machine learning techniques to predict different levels of hospital care of CoVid-19
Applied Intelligence, Vol. 52, Núm. 6, pp. 6413-6431
2021
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Dealing with heterogeneity in the context of distributed feature selection for classification
Knowledge and Information Systems, Vol. 63, Núm. 1, pp. 233-276
2020
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A delayed elastic-net approach for performing adversarial attacks
Proceedings - International Conference on Pattern Recognition
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A scalable saliency-based feature selection method with instance-level information
Knowledge-Based Systems, Vol. 192
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Can data placement be effective for Neural Networks classification tasks? Introducing the orthogonal loss
Proceedings - International Conference on Pattern Recognition
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Do we need hundreds of classifiers or a good feature selection?
ESANN 2020 - Proceedings, 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
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Feature selection with limited bit depth mutual information for portable embedded systems
Knowledge-Based Systems, Vol. 197
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Importance of coding co-morbidities for APR-DRG assignment: Focus on cardiovascular and respiratory diseases
Health Information Management Journal, Vol. 49, Núm. 1, pp. 47-57