2 papers
cs.LG2025
PracMHBench: Re-evaluating Model-Heterogeneous Federated Learning Based on Practical Edge Device Constraints
Yuanchun Guo, Bingyan Liu, Yulong Sha +1
Federating heterogeneous models on edge devices with diverse resource constraints has been a notable trend in recent years. Compared to traditional federated learning (FL) that ass…
cs.LG2025
BTFL: A Bayesian-based Test-Time Generalization Method for Internal and External Data Distributions in Federated learning
Yu Zhou, Bingyan Liu
Federated Learning (FL) enables multiple clients to collaboratively develop a global model while maintaining data privacy. However, online FL deployment faces challenges due to dis…