文献
J-GLOBAL ID:202202288426828868
整理番号:22A0651178
連合学習におけるデバイス不均一性に起因する局所エポック非効率性【JST・京大機械翻訳】
Local Epochs Inefficiency Caused by Device Heterogeneity in Federated Learning
著者 (9件):
Zeng Yan
(School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China)
,
Zeng Yan
(Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education, Hangzhou 310018, China)
,
Zeng Yan
(Zhejiang Engineering Research Center of Data Security Governance, Hangzhou 310018, China)
,
Wang Xin
(HDU-ITMO Joint Institute, Hangzhou Dianzi University, Hangzhou 310018, China)
,
Yuan Junfeng
(School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China)
,
Zhang Jilin
(School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China)
,
Zhang Jilin
(Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education, Hangzhou 310018, China)
,
Zhang Jilin
(Zhejiang Engineering Research Center of Data Security Governance, Hangzhou 310018, China)
,
Wan Jian
(School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China)
資料名:
Wireless Communications & Mobile Computing
(Wireless Communications & Mobile Computing)
巻:
2022
ページ:
Null
発行年:
2022年
JST資料番号:
W1338A
ISSN:
1530-8669
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
イギリス (GBR)
言語:
英語 (EN)