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Autor:
Boussetta, Amine, El Mhamdi, El Mahdi, Guerraoui, Rachid, Maurer, Alexandre David Olivier, Rouault, Sébastien Louis Alexandre
Modern machine learning architectures distinguish servers and workers. Typically, a d-dimensional model is hosted by a server and trained by n workers, using a distributed stochastic gradient descent (SGD) optimization scheme. At each SGD step, the g
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efe8e6c94dc0e5e161f4ca4d542e347e
The increasing prevalence of personal devices motivates the design of algorithms that can leverage their computing power, together with the data they generate, in order to build privacy-preserving and effective machine learning models. However, tradi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______185::4519ec3351136bc35576638211b15fda
https://infoscience.epfl.ch/record/300949
https://infoscience.epfl.ch/record/300949
Autor:
Hadj Henni A; Radiation Oncology Department, Centre Frederic Joliot, Rouen, France., Arhoun I; Radiation Oncology Department, Centre Frederic Joliot, Rouen, France., Boussetta A; Mohammed VI Polytechnic University, Ben Guerir, Morocco., Daou W; Mohammed VI Polytechnic University, Ben Guerir, Morocco., Marque A; Radiation Oncology Department, Centre Frederic Joliot, Rouen, France.; Oncology Department, Clinique Saint Hilaire, Rouen, France.
Publikováno v:
Frontiers in oncology [Front Oncol] 2024 Jan 17; Vol. 14, pp. 1320002. Date of Electronic Publication: 2024 Jan 17 (Print Publication: 2024).
