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Monitoring, understanding, and optimizing the energy consumption of Machine Learning (ML) are various reasons why it is necessary to evaluate the energy usage of ML. However, there exists no universal tool that can answer this question for all use ca
Externí odkaz:
http://arxiv.org/abs/2408.15128
Autor:
Cremonesi, Francesco, Vesin, Marc, Cansiz, Sergen, Bouillard, Yannick, Balelli, Irene, Innocenti, Lucia, Silva, Santiago, Ayed, Samy-Safwan, Taiello, Riccardo, Kameni, Laetita, Vidal, Richard, Orlhac, Fanny, Nioche, Christophe, Lapel, Nathan, Houis, Bastien, Modzelewski, Romain, Humbert, Olivier, Önen, Melek, Lorenzi, Marco
The real-world implementation of federated learning is complex and requires research and development actions at the crossroad between different domains ranging from data science, to software programming, networking, and security. While today several
Externí odkaz:
http://arxiv.org/abs/2304.12012
Autor:
Lionel E. Kameni, Michelle Griffin, Charlotte E. Berry, Siavash Shariatzadeh, Mauricio A. Downer, Caleb Valencia, Alexander Z. Fazilat, Rahim Nazerali, Arash Momeni, Michael Januszyk, Michael T. Longaker, Derrick C. Wan
Publikováno v:
Radiation Oncology, Vol 19, Iss 1, Pp 1-11 (2024)
Abstract Background Radiation-induced fibrosis (RIF) is an important late complication of radiation therapy, and the resulting damaging effects of RIF can significantly impact reconstructive outcomes. There is currently a paucity of effective treatme
Externí odkaz:
https://doaj.org/article/3862a0fca96248d395f820734d5b70a1
Federated learning (FL) is an effective solution to train machine learning models on the increasing amount of data generated by IoT devices and smartphones while keeping such data localized. Most previous work on federated learning assumes that clien
Externí odkaz:
http://arxiv.org/abs/2301.01542
Publikováno v:
Acta Herpetologica (2024)
African skinks of the genus Trachylepis is one of the most diverse genera of lizards in Africa. Although, many species have not been validated phylogenetically in recent years. In this study we evaluate the phylogenetic status of the Cameroon Volcani
Externí odkaz:
https://doaj.org/article/686148c709c84297a9e56cd8838e1313
Autor:
Patrice Djataou, Marceline Djuidje Ngounoue, Carine Nguefeu Nkenfou-Tchinda, Marie Nicole Ngoufack, Elise Elong, Aline Tiga, Clifford Muluh, Joelle Kadji Kameni, Moussa Djaouda, Alexis Ndjolo, Celine Nguefeu Nkenfou
Publikováno v:
Frontiers in Genetics, Vol 15 (2024)
BackgroundHIV infection and its progression to AIDS depend on several factors including host genetic factors. The immunological mechanisms of host resistance to HIV infection greatly influence the prevalence of HIV in a given region. Worldwide, Camer
Externí odkaz:
https://doaj.org/article/c4eb3373a36e4eb9b29448317980aa92
Autor:
Armel Zambou Kenfack, Modeste Kameni Nematchoua, Elie Simo, Ghislain Junior Bangoup Ntegmi, Venant Sorel Chara-Dackou
Publikováno v:
Heliyon, Vol 10, Iss 17, Pp e37099- (2024)
With the aim of diversifying different energy sources and achieving net zero emissions, hybrid renewable energy sources (HRES) represent the future of the world. However, several HRES simulation software do not integrate the Photovoltaic/thermal (PV/
Externí odkaz:
https://doaj.org/article/7e93a31c2f6842d7a61153fd37894ad7
Autor:
Fraboni, Yann, Van Waerebeke, Martin, Scaman, Kevin, Vidal, Richard, Kameni, Laetitia, Lorenzi, Marco
Machine Unlearning (MU) is an increasingly important topic in machine learning safety, aiming at removing the contribution of a given data point from a training procedure. Federated Unlearning (FU) consists in extending MU to unlearn a given client's
Externí odkaz:
http://arxiv.org/abs/2211.11656
We propose a novel framework to study asynchronous federated learning optimization with delays in gradient updates. Our theoretical framework extends the standard FedAvg aggregation scheme by introducing stochastic aggregation weights to represent th
Externí odkaz:
http://arxiv.org/abs/2206.10189
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 102920- (2024)
In order to achieve a sustainable, low-carbon energy future, it is necessary to develop innovative and integrated solutions. However, one of the main obstacles to the advancement of renewable energy is storage. With this in mind, hybrid systems combi
Externí odkaz:
https://doaj.org/article/60587fdb407c4deaaa8e5160fc69c2fb