Apprentissage non supervisé pour données extrêmement volumineuses en situation de ressources informatiques arbitrairement limitées

Autor: Antonazzo, Filippo

Publikováno v: Data Structures and Algorithms [cs.DS]. Université de Lille, 2022. English. ⟨NNT : 2022ULILB015⟩
Statistics [math.ST]. Université de Lille, 2022. English. ⟨NNT : ⟩

Clustering reveals all its interest when the data set size considerably increases, since there is the opportunity to discover tiny but possibly high value clusters, which can not be detected with moderate sample sizes. However, the clustering of such

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3fe75bf7693d2ff1066ed2d94bec5b7a
https://theses.hal.science/tel-03846222

A binned technique for scalable model-based clustering on huge datasets

Autor: Antonazzo, Filippo, Biernacki, Christophe, Keribin, Christine

Publikováno v: MBC2-Models and Learning for Clustering and Classification
MBC2-Models and Learning for Clustering and Classification, Sep 2020, Catania, Italy
Book of Short Papers of the 5th international workshop on Models and Learning for Clustering and Classification MBC2 2020, Catania, Italy
Book of Short Papers of the 5th international workshop on Models and Learning for Clustering and Classification MBC2 2020, Catania, Italy, pp.11-16, 2021

International audience; Clustering is impacted by the regular increase of sample sizes which provides opportunity to reveal information previously out of scope. However, the volume of data leads to some issues related to the need of many computationa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::1b1403388e46dbbdcd758a094d53e005
https://hal.archives-ouvertes.fr/hal-03097284/document

Estimation de modèles de mélanges gaussiens univariés à partir de données groupées dans le cas d'une grande volumétrie de données

Autor: Antonazzo, Filippo, Biernacki, Christophe, Keribin, Christine

Publikováno v: SFdS 2021-52èmes Journées de Statistiques de la Société Française de Statistique
SFdS 2021-52èmes Journées de Statistiques de la Société Française de Statistique, May 2020, Nice, France

Due to the COVID-19 pandemic, the 52nd Journées de Statistique are postponed. They will take place from June 7th to 11th 2021 in Nice on the Valrose Campus of the Université Côte d'Azur.; National audience; Popularity of unsupervised learning is m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a09a67886e05d12da319bd11bf97810d
https://hal.inria.fr/hal-03082437/document

Optical coherence tomography in adult adrenoleukodystrophy: a cross-sectional and longitudinal study.

Autor: Bianchi-Marzoli, Stefania, Fenu, Silvia, Melzi, Lisa, Benzoni, Chiara, Antonazzo, Filippo, Tomas Roldan, Eugenia, Farina, Laura, Tremolada, Gemma, Mauro, Elena, Pensato, Viviana, Gellera, Cinzia, Pareyson, Davide, Salsano, Ettore

Publikováno v: Neurological Sciences; 2021, Vol. 42 Issue 1, p235-241, 7p, 4 Charts