Zobrazeno 1 - 10
of 1 526
pro vyhledávání: '"Li, GY"'
Publikováno v:
Therapeutics and Clinical Risk Management, Vol Volume 20, Pp 39-45 (2024)
Da-Quan Wu,1,* Shu-Yang Chen,1,* Ke-Guang Chen,1 Tan Wang,1 Guang-Yao Li,2 Xin-Sheng Huang1 1Otolaryngology Head and Neck Surgery, Zhongshan Hospital, Shanghai, 200032, People’s Republic of China; 2Department of Otolaryngology, Eye & ENT Ho
Externí odkaz:
https://doaj.org/article/462418fe60cf436a89c4272186bc30be
Publikováno v:
Therapeutics and Clinical Risk Management, Vol Volume 18, Pp 879-887 (2022)
Hong-Qin Wei,1 Man Gan,1 Guo-Yan Li,2 Sui-Hong Ma,1 Jian-Hua Liu1 1Department of Ultrasound, Guangzhou First People’s Hospital, Guangzhou, Guandong, People’s Republic of China; 2Department of Rehabilitation Medicine, Guangzhou First People’s Ho
Externí odkaz:
https://doaj.org/article/23d760c1ad2e4960accbf3bdd1b1553e
Publikováno v:
Journal of Tropical Forest Science, 2015 Jul 01. 27(3), 369-375.
Externí odkaz:
https://www.jstor.org/stable/43490295
Publikováno v:
In Advances in Medical Sciences 1 June 2013 58(1):112-117
Publikováno v:
IEEE Transactions on Signal Processing. 69:1124-1139
The potential benefits of massive multiple-input multiple-output (MIMO) make it possible to achieve high-quality underwater acoustic (UWA) communications. Nevertheless, due to the wideband nature of UWA channels, existing massive MIMO techniques for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::52a3d3e96646039471bc9fa2fa105303
https://doi.org/10.1109/tsp.2021.3050037
https://doi.org/10.1109/tsp.2021.3050037
One of the crucial issues in federated learning is how to develop efficient optimization algorithms. Most of the current ones require full devices participation and/or impose strong assumptions for convergence. Different from the widely-used gradient
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1032::5db85a761e267dbd658720838fd78dd7
http://hdl.handle.net/10044/1/97445
http://hdl.handle.net/10044/1/97445
Federated learning has shown its advances over the last few years but is facing many challenges, such as how algorithms save communication resources, how they reduce computational costs, and whether they converge. To address these issues, this paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1032::4d7eee135b6cb59d8208c1ed670069a1
http://hdl.handle.net/10044/1/99531
http://hdl.handle.net/10044/1/99531
Publikováno v:
Journal of Tropical Forest Science, 2011 Jan 01. 23(1), 51-56.
Externí odkaz:
https://www.jstor.org/stable/23616879
Federated learning has shown its advances over the last few years but is facing many challenges, such as how algorithms save communication resources, how they reduce computational costs, and whether they converge. To address these issues, this paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1032::69ad68287b1f449dc798a186f61fd117
http://hdl.handle.net/10044/1/93550
http://hdl.handle.net/10044/1/93550
Publikováno v:
Open Chemistry, Vol 16, Iss 1, Pp 1257-1267 (2018)
A microRNA (miRNA) nanomedicine PEG-PEI/miR-221/222 was synthesized based on PEGylated polyethylenimine PEG-PEI and used to transfect prostate cancer cells (PC-3) in vitro. Gel retardation assay confirmed the formation of nanomedicine, of which the z
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::156459234a9194b8869e76acca05ca15
https://doaj.org/article/0ee3e5a6d6084a38bc1087bfcd8803b2
https://doaj.org/article/0ee3e5a6d6084a38bc1087bfcd8803b2