IEEE

Private Sample Alignment for Vertical Federated Learning: An Efficient and Reliable Realization

Abstract: Sample alignment is recognized as a vital component of vertical federated learning, which facilitates the integration of differential samples and high-quality model training. In this trend, ...
IEEE

Noise-Robust Federated Learning With Model Heterogeneous Clients

Abstract: Federated Learning (FL) enables multiple devices to collaboratively train models without sharing their raw data. Considering that clients may prefer to design their own models independently, ...
EurekAlert!

A federated anti-forgetting representation method based on hybrid model architecture and gradient truncation

Anti-forgetting representation learning method reduces the weight aggregation interference on model memory and augments the ...
GitHub

patkilleen/fed_learn_yield_prediction_2025

This is the official documentation of the code repository of the paper: Patrick Killeen, Iluju Kiringa, and Tet Yeap "UAV Imagery-Based Yield Prediction Using Distributed Machine Learning via Model ...