Quantized federated learning under transmission delay and outage constraints
Federated learning (FL) has been recognized as a viable distributed learning paradigm
which trains a machine learning model collaboratively with massive mobile devices in the …
which trains a machine learning model collaboratively with massive mobile devices in the …
Autonomous transportation systems and services enabled by the next-generation network
The vast development of the next-generation network (NGN) impels its integration with
emerging technologies, such as big data, artificial intelligence, and federated learning, to …
emerging technologies, such as big data, artificial intelligence, and federated learning, to …
FedHD: Communication-efficient federated learning from hybrid data
H Gao, S Ge, TH Chang - Journal of the Franklin Institute, 2023 - Elsevier
Federated learning (FL) has attracted significant attention in the machine learning
community owing to its instinct local privacy awareness. Depending on how the data are …
community owing to its instinct local privacy awareness. Depending on how the data are …
A general solution for straggler effect and unreliable communication in federated learning
The straggler effect is the main bottleneck for Federated Learning (FL), where the
performance of training is degraded by the slowest member. Another significant problem is …
performance of training is degraded by the slowest member. Another significant problem is …
Provision for Energy: A Resource Allocation Problem in Federated Learning for Edge Systems
M Liu, L Rajamanickam - 2023 - researchsquare.com
The article explores an energy-efficient method for allocating transmission and computation
resources for federated learning (FL) on wireless communication networks. The model being …
resources for federated learning (FL) on wireless communication networks. The model being …