Zobrazeno 1 - 10
of 27 666
pro vyhledávání: '"Canini A."'
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Guazzelli Filho, Eloar
Este trabalho de pesquisa estuda um autor - Renato Canini - que construiu uma trajetória peculiar ao desenvolver uma narrativa de histórias em quadrinhos com um traço bastante pessoal apesar de inserida nas de estruturas de produção massivas. En
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Valenciano, Alberto1,2,3 (AUTHOR) a.valenciano@unizar.es, Morales, Jorge4 (AUTHOR), Govender, Romala1,2 (AUTHOR)
Publikováno v:
Zoological Journal of the Linnean Society. Feb2022, Vol. 194 Issue 2, p366-394. 29p.
Autor:
Samuele Frosali, Saverio Bartolini-Lucenti, Joan Madurell-Malapeira, Alessandro Urciuoli, Loïc Costeur, Lorenzo Rook
Publikováno v:
Frontiers in Ecology and Evolution, Vol 11 (2023)
IntroductionThe phylogenetic and ecological importance of paranasal sinuses in carnivorans was highlighted by several previous authors, mostly in extant species. Nevertheless, no specific study on this feature on extant canids, and no one on fossil r
Externí odkaz:
https://doaj.org/article/066a8ccf32cb4c64a71267b6933bf882
Autor:
Çakır, Mustafa Sefa1 mscakir@cumhuriyet.edu.tr
Publikováno v:
Faculty of Letters Journal of Social Sciences / Cumhuriyet Üniversitesi Sosyal Bilimler Dergisi. haz2021, Vol. 45 Issue 1, p49-65. 17p.
Progressing beyond centralized AI is of paramount importance, yet, distributed AI solutions, in particular various federated learning (FL) algorithms, are often not comprehensively assessed, which prevents the research community from identifying the
Externí odkaz:
http://arxiv.org/abs/2407.14154
This work tackles the challenges of data heterogeneity and communication limitations in decentralized federated learning. We focus on creating a collaboration graph that guides each client in selecting suitable collaborators for training personalized
Externí odkaz:
http://arxiv.org/abs/2406.06520
We propose NeuronaBox, a flexible, user-friendly, and high-fidelity approach to emulate DNN training workloads. We argue that to accurately observe performance, it is possible to execute the training workload on a subset of real nodes and emulate the
Externí odkaz:
http://arxiv.org/abs/2405.02969
Autor:
Brookes, Anne
Publikováno v:
The Burlington Magazine, 2008 Jul 01. 150(1264), 478-478.
Externí odkaz:
https://www.jstor.org/stable/40479806