1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning
Divyansh Jhunjhunwala, Pranay Sharma, Zheng Xu +1
Initializing with pre-trained models when learning on downstream tasks is becoming standard practice in machine learning. Several recent works explore the benefits of pre-trained i…
cs.LG2024
Debiasing Federated Learning with Correlated Client Participation
Zhenyu Sun, Ziyang Zhang, Zheng Xu +3
In cross-device federated learning (FL) with millions of mobile clients, only a small subset of clients participate in training in every communication round, and Federated Averagin…
cs.LG2024★ 1 cited
Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models
Yae Jee Cho, Luyang Liu, Zheng Xu +2
Foundation models (FMs) adapt well to specific domains or tasks with fine-tuning, and federated learning (FL) enables the potential for privacy-preserving fine-tuning of the FMs wi…