1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Biased Over-the-Air Federated Learning under Wireless Heterogeneity
Muhammad Faraz Ul Abrar, Nicolò Michelusi
Recently, Over-the-Air (OTA) computation has emerged as a promising federated learning (FL) paradigm that leverages the waveform superposition properties of the wireless channel to…
cs.LG2024★ 1 cited
Analog-digital Scheduling for Federated Learning: A Communication-Efficient Approach
Muhammad Faraz Ul Abrar, Nicolò Michelusi
Over-the-air (OTA) computation has recently emerged as a communication-efficient Federated Learning (FL) paradigm to train machine learning models over wireless networks. However,…