AUCTION: Automated and Quality-Aware Client Selection Framework for Efficient Federated Learning

The emergency of federated learning (FL) enables distributed data owners to collaboratively build a global model without sharing their raw data, which creates a new business chance for building data market. However, in practical FL scenarios, the hardware conditions and data resources of the partici...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IEEE transactions on parallel and distributed systems Ročník 33; číslo 8; s. 1996 - 2009
Hlavní autori:	Deng, Yongheng, Lyu, Feng, Ren, Ju, Wu, Huaqing, Zhou, Yuezhi, Zhang, Yaoxue, Shen, Xuemin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Artificial neural networks Budgets client selection Clients Coders Collaborative work Data integrity Data models Data privacy data quality Design factors Distributed databases distributed system Encoders-Decoders Federated learning Machine learning Neural networks reinforcement learning Task analysis Training
ISSN:	1045-9219, 1558-2183
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!