Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning

Sun，Jun1; Chen，Tianyi2; Giannakis，Georgios B.3; Yang，Qinmin1; Yang，Zaiyue4

2022-04-01

10.1109/TPAMI.2020.3033286

IEEE Transactions on Pattern Analysis and Machine Intelligence   影响因子和分区

1939-3539

Federated learning communication-efficient gradient innovation quantization

SCI ; EI

其他

20221111789809

Gradient methods

Control Systems:731.1 ; Numerical Methods:921.6 ; Systems Science:961

ENGINEERING

IEEE

1.State Key Laboratory of Industrial Control Technology,College of Control Science and Engineering,Zhejiang University,Hangzhou,310027,China
2.Department of Electrical Computer and Systems Engineering,Rensselaer Polytechnic Institute,Troy,12180,United States
3.Department of Electrical and Computer Engineering,Digital Technology Center,University of Minnesota,Minneapolis,55455,United States
4.Department of Mechanical and Energy Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Sun，Jun,Chen，Tianyi,Giannakis，Georgios B.,et al. Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2022,44(4):2031-2044.

Sun，Jun,Chen，Tianyi,Giannakis，Georgios B.,Yang，Qinmin,&Yang，Zaiyue.(2022).Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning.IEEE Transactions on Pattern Analysis and Machine Intelligence,44(4),2031-2044.

Sun，Jun,et al."Lazily Aggregated Quantized Gradient Innovation for Communication-Efficient Federated Learning".IEEE Transactions on Pattern Analysis and Machine Intelligence 44.4(2022):2031-2044.