Zobrazeno 1 - 10
of 334
pro vyhledávání: '"A. Fertakis"'
Autor:
DeCoster, Don T.1 (AUTHOR), Fertakis, John P.2 (AUTHOR)
Publikováno v:
Journal of Accounting Research (Wiley-Blackwell). Autumn68, Vol. 6 Issue 2, p237-246. 10p. 1 Chart.
Publikováno v:
Perspectives on Research in Emotional Stress ISBN: 9781315075488
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57f2ed67d240aa26cc34209928e3f16b
https://doi.org/10.4324/9781315075488-10
https://doi.org/10.4324/9781315075488-10
Autor:
Fertakis, John P.
Publikováno v:
The Accounting Review, 1970 Jul 01. 45(3), 509-512.
Externí odkaz:
https://www.jstor.org/stable/243848
Autor:
Fertakis, John P.
Publikováno v:
The Accounting Review, 1969 Oct 01. 44(4), 680-691.
Externí odkaz:
https://www.jstor.org/stable/243669
Autor:
Kapotis, Ch., Tsomi, A., Babionitakis, A., Grammenou, G., Kosmaoglou, E., Pardalidis, N., Troupis, T., Fertakis, A.
Publikováno v:
Human Heredity, 1998 Jan 01. 48(3), 155-157.
Externí odkaz:
https://www.jstor.org/stable/48506503
Autor:
Mai, Luo, Li, Guo, Wagenländer, Marcel, Fertakis, Konstantinos, Brabete, Andrei-Octavian, Pietzuch, Peter
Publikováno v:
USENIX Symposium on Operating Systems Design and Implementation (OSDI)
Mai, L, Li, G, Wagenländer, M, Fertakis, K, Brabete, A-O & Pietzuch, P 2020, KungFu: Making Training in Distributed Machine Learning Adaptive . in 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20) . pp. 937-954, 14th USENIX Symposium on Operating Systems Design and Implementation, Banff, Canada, 4/11/20 . < https://www.usenix.org/conference/osdi20/presentation/mai >
Mai, L, Li, G, Wagenländer, M, Fertakis, K, Brabete, A-O & Pietzuch, P 2020, KungFu: Making Training in Distributed Machine Learning Adaptive . in 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI 20) . pp. 937-954, 14th USENIX Symposium on Operating Systems Design and Implementation, Banff, Canada, 4/11/20 . < https://www.usenix.org/conference/osdi20/presentation/mai >
When using distributed machine learning (ML) systems to train models on a cluster of worker machines, users must configure a large number of parameters: hyper-parameters (e.g. the batch size and the learning rate) affect model convergence; system par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::4c8ec2dc41bd263f027e7cd1c511946b
http://hdl.handle.net/10044/1/85597
http://hdl.handle.net/10044/1/85597
Publikováno v:
CloudCom
The use of accelerators in computing facilities that employ heterogeneity in order to achieve higher performance has become prominent in the past years. Accelerators lie on the hearts of modern data center and computing facilities, powering the major
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1d645e1bb95697fc3aef2de4da132a8
https://doi.org/10.1109/cloudcom2018.2018.00049
https://doi.org/10.1109/cloudcom2018.2018.00049
Autor:
Solomou, E., Tsanaktsi, A., Fertakis, V., Dallas, K., Karambina, S., Tiniakou, M., Kourakli, A., Micheva, I., Matsouka, P., Zoumbos, N.
Publikováno v:
In Leukemia Research 2009 33 Supplement 1:S95-S95
Autor:
Voukelatou, G., Thanopoulou, E., Dallas, K., Fertakis, V., Dimopoulou, A., Micheva, I., Lampropoulou, P., Kouraklis-Symeonidis, A., Symeonidis, A., Zoumbos, N.
Publikováno v:
In Leukemia Research 2009 33 Supplement 1:S93-S94
Publikováno v:
In Leukemia Research 2009 33 Supplement 1:S57-S58