Gaël Beck
Orcid: 0000-0002-5228-2666
According to our database1,
Gaël Beck
authored at least 14 papers
between 2016 and 2021.
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Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2021
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021
2020
A scalable and effective rough set theory-based approach for big data pre-processing.
Knowl. Inf. Syst., 2020
2019
Scalable Clustering Applying Local Accretions. (Accrétions Locales appliquées au Clustering Scalable et Distribué).
PhD thesis, 2019
A distributed approximate nearest neighbors algorithm for efficient large scale mean shift clustering.
J. Parallel Distributed Comput., 2019
A Distributed and Approximated Nearest Neighbors Algorithm for an Efficient Large Scale Mean Shift Clustering.
CoRR, 2019
Proceedings of the Trends and Applications in Knowledge Discovery and Data Mining, 2019
2018
Proceedings of the INNS Conference on Big Data and Deep Learning 2018, 2018
Nouveau Modèle de Sélection de Caractéristiques basé sur la Théorie des Ensembles Approximatifs pour les Données Massives.
Proceedings of the Extraction et Gestion des Connaissances, 2018
Proceedings of the Extraction et Gestion des Connaissances, 2018
A Distributed Rough Set Theory Algorithm based on Locality Sensitive Hashing for an Efficient Big Data Pre-processing.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018
2017
A distributed rough set theory based algorithm for an efficient big data pre-processing under the spark framework.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017
2016
Nearest neighbour estimators of density derivatives, with application to mean shift clustering.
Pattern Recognit. Lett., 2016
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016