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Early experiences of noise-sensitivity performance analysis of a distributed deep learning framework

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dc.contributor.authorRojas, Elvis
dc.contributor.authorKnobloch, Michael
dc.contributor.authorDaoud, Nour
dc.contributor.authorMeneses, Esteban
dc.contributor.authorMohr, Bernd
dc.date.accessioned2026-03-20T20:32:06Z
dc.date.available2026-03-20T20:32:06Z
dc.date.issued2022
dc.identifier.doidoi: 10.1109/CLUSTER51413.2022.00066
dc.identifier.urihttps://hdl.handle.net/20.500.12337/11568
dc.language.isoen_US
dc.publisher2022 IEEE International Conference on Cluster Computing (CLUSTER)
dc.relationdoi: 10.1109/CLUSTER51413.2022.00066
dc.rightsacceso restringido
dc.sourceIEEE International Conference on Cluster Computing (CLUSTER), Heidelberg, Germany, 2022, pp. 516-522
dc.subjectREDES NEURONALES
dc.subjectCOMPUTACIÓN
dc.subjectAPRENDIZAJE PROFUNDO
dc.titleEarly experiences of noise-sensitivity performance analysis of a distributed deep learning framework
dc.typeartículo de investigación

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