Self-Balancing Federated Learning With Global Imbalanced Data in Mobile Systems

Federated learning (FL) is a distributed deep learning method that enables multiple participants, such as mobile and IoT devices, to contribute a neural network while their private training data remains in local devices. This distributed approach is promising in the mobile systems where have a large...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on parallel and distributed systems Ročník 32; číslo 1; s. 59 - 71
Hlavní autoři:	Duan, Moming, Liu, Duo, Chen, Xianzhang, Liu, Renping, Tan, Yujuan, Liang, Liang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Algorithms Balancing Communications traffic Data augmentation Data models Datasets Distributed databases distributed machine learning Electronic devices Federated learning Machine learning Mobile communication systems Mobile handsets Neural networks Privacy Rescheduling Servers Training
ISSN:	1045-9219, 1558-2183
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!