3 papers
cs.LG2025
Private Federated Learning In Real World Application -- A Case Study
An Ji, Bortik Bandyopadhyay, Congzheng Song +7
This paper presents an implementation of machine learning model training using private federated learning (PFL) on edge devices. We introduce a novel framework that uses PFL to add…
cs.LG2024
pfl-research: simulation framework for accelerating research in Private Federated Learning
Filip Granqvist, Congzheng Song, Ãine Cahill +7
Federated learning (FL) is an emerging machine learning (ML) training paradigm where clients own their data and collaborate to train a global model, without revealing any data to t…
cs.LG2024
Momentum Approximation in Asynchronous Private Federated Learning
Tao Yu, Congzheng Song, Jianyu Wang +1
Asynchronous protocols have been shown to improve the scalability of federated learning (FL) with a massive number of clients. Meanwhile, momentum-based methods can achieve the bes…