Robust Federated Learning for Unreliable and Resource-limited Wireless Networks
Federated learning (FL) is an efficient and privacy-preserving distributed learning paradigm
that enables massive edge devices to train machine learning models collaboratively …
that enables massive edge devices to train machine learning models collaboratively …
Performance Comparison Between Coherent and Non-Coherent Approaches for Over-the-Air Computation
Over-the-air computation (OAC) can effectively support rapid data aggregation from a
plethora of devices, exploiting the inherent superposition property of wireless multiple …
plethora of devices, exploiting the inherent superposition property of wireless multiple …
Exploring Communication Efficient Strategies in Federated Learning Systems
Federated learning is a distributed learning paradigm that enables various lightweight
devices in distributed networks, such as edge devices, to collaboratively generate a …
devices in distributed networks, such as edge devices, to collaboratively generate a …