2 papers
cs.LG2024
FedQP: Towards Accurate Federated Learning using Quadratic Programming Guided Mutation
Jiawen Weng, Zeke Xia, Ran Li +2
Due to the advantages of privacy-preserving, Federated Learning (FL) is widely used in distributed machine learning systems. However, existing FL methods suffer from low-inference…
cs.LG2024
Personalized Federated Instruction Tuning via Neural Architecture Search
Pengyu Zhang, Yingbo Zhou, Ming Hu +3
Federated Instruction Tuning (FIT) has shown the ability to achieve collaborative model instruction tuning among massive data owners without sharing private data. However, it still…