most citedByzantine-Robust Federated Learning with Variance Reduction and Differential Privacy

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2025

Fed-HeLLo: Efficient Federated Foundation Model Fine-Tuning with Heterogeneous LoRA Allocation

Zikai Zhang, Ping Liu, Jiahao Xu +1

Federated Learning has recently been utilized to collaboratively fine-tune foundation models across multiple clients. Notably, federated low-rank adaptation LoRA-based fine-tuning…

cs.LG2023★ 1 cited

Byzantine-Robust Federated Learning with Variance Reduction and Differential Privacy

Zikai Zhang, Rui Hu

Federated learning (FL) is designed to preserve data privacy during model training, where the data remains on the client side (i.e., IoT devices), and only model updates of clients…