K -MLIO: Enabling K -Means for Large Data-Sets and Memory Constrained Embedded Systems - Université de Bretagne Occidentale
Conference Papers Year : 2019

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

Camelia Slimani
  • Function : Author
Lab-STICC_UBO_CACS_MOCS
Stéphane Rubini
Lab-STICC_UBO_CACS_MOCS
Jalil Boukhobza
Lab-STICC_UBO_CACS_MOCS
CV

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Operating Systems [cs.OS] Embedded Systems Artificial Intelligence [cs.AI]

Jalil Boukhobza  : Connect in order to contact the contributor

https://hal.univ-brest.fr/hal-02482026

Submitted on : Monday, February 17, 2020-5:57:08 PM

Last modification on : Tuesday, August 27, 2024-12:51:33 PM

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hal-02482026 , version 1 (17-02-2020)

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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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