4 papers · 1 filter
Convergence Analysis of Aggregation-Broadcast in LoRA-enabled Distributed Fine-Tuning
Xin Chen, Shuaijun Chen, Omid Tavallaie +3
Federated Learning (FL) enables collaborative model training across decentralized data sources while preserving data privacy. However, the growing size of Machine Learning (ML) mod…
Personalizing Federated Learning for Hierarchical Edge Networks with Non-IID Data
Seunghyun Lee, Omid Tavallaie, Shuaijun Chen +4
Accommodating edge networks between IoT devices and the cloud server in Hierarchical Federated Learning (HFL) enhances communication efficiency without compromising data privacy. H…
AutoRank: MCDA Based Rank Personalization for LoRA-Enabled Distributed Learning
Shuaijun Chen, Omid Tavallaie, Niousha Nazemi +2
As data volumes expand rapidly, distributed machine learning has become essential for addressing the growing computational demands of modern AI systems. However, training models in…
RBLA: Rank-Based-LoRA-Aggregation for Fine-tuning Heterogeneous Models in FLaaS
Shuaijun Chen, Omid Tavallaie, Niousha Nazemi +1
Federated Learning (FL) is a promising privacy-aware distributed learning framework that can be deployed on various devices, such as mobile phones, desktops, and devices equipped w…