Gaël Beck

Orcid: 0000-0002-5228-2666

According to our database1, Gaël Beck authored at least 14 papers between 2016 and 2021.

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

Timeline

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Bibliography

2021
A New Nearest Neighbor Median Shift Clustering for Binary Data.
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

Nearest Neighbor Median Shift Clustering for Binary Data.
CoRR, 2019

A Distributed and Approximated Nearest Neighbors Algorithm for an Efficient Large Scale Mean Shift Clustering.
CoRR, 2019

Algorithms for an Efficient Tensor Biclustering.
Proceedings of the Trends and Applications in Knowledge Discovery and Data Mining, 2019

2018
A New Micro-Batch Approach for Partial Least Square Clusterwise Regression.
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

Mean-shift : Clustering scalable et distribué.
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

Distributed mean shift clustering with approximate nearest neighbours.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016


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