Qingsong Wei

CE-Fed: Communication efficient multi-party computation enabled federated learning

2022 · Array

Federated learning (FL) allows a number of parties collectively train models without revealing private datasets. There is a possibility of extracting personal or confidential data from the shared models even-though sharing of raw data is …

An Aggregation-Free Federated Learning for Tackling Data Heterogeneity

2024 · arXiv (Cornell University)

The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framework, where clients update local models based on a global model aggregated by …