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Conference papers

K -MLIO: Enabling K -Means for Large Data-Sets and Memory Constrained Embedded Systems

Camelia Slimani 1 Stéphane Rubini 2 Jalil Boukhobza 2
1 Lab-STICC_UBO_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance, IBNM - Institut Brestois du Numérique et des Mathématiques
2 Lab-STICC_UBO_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance, UBO - Université de Brest
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https://hal.univ-brest.fr/hal-02482026
Contributor : Jalil Boukhobza Connect in order to contact the contributor
Submitted on : Monday, February 17, 2020 - 5:57:08 PM
Last modification on : Monday, April 4, 2022 - 9:28:18 AM

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Camelia Slimani, Stéphane Rubini, Jalil Boukhobza. K -MLIO: Enabling K -Means for Large Data-Sets and Memory Constrained Embedded Systems. 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), Oct 2019, Rennes, France. pp.262-268, ⟨10.1109/MASCOTS.2019.00037⟩. ⟨hal-02482026⟩

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