27 citations · 27 across the 4 of their papers we have counts for
4 papers · 1 filter
GAS: Generative Activation-Aided Asynchronous Split Federated Learning
Jiarong Yang, Yuan Liu
Split Federated Learning (SFL) splits and collaboratively trains a shared model between clients and server, where clients transmit activations and client-side models to server for…
SCALA: Split Federated Learning with Concatenated Activations and Logit Adjustments
Jiarong Yang, Yuan Liu
Split Federated Learning (SFL) is a distributed machine learning framework which strategically divides the learning process between a server and clients and collaboratively trains…
Asynchronous Wireless Federated Learning with Probabilistic Client Selection
Jiarong Yang, Yuan Liu, Fangjiong Chen +2
Federated learning (FL) is a promising distributed learning framework where distributed clients collaboratively train a machine learning model coordinated by a server. To tackle th…
Client Selection for Federated Bayesian Learning
Jiarong Yang, Yuan Liu, Rahif Kassab
Distributed Stein Variational Gradient Descent (DSVGD) is a non-parametric distributed learning framework for federated Bayesian learning, where multiple clients jointly train a ma…