3 papers
cs.CR2025
Secure Aggregation in Federated Learning using Multiparty Homomorphic Encryption
Erfan Hosseini, Shuangyi Chen, Ashish Khisti
A key operation in federated learning is the aggregation of gradient vectors generated by individual client nodes. We develop a method based on multiparty homomorphic encryption (M…
cs.LG2025
Robust Federated Finetuning of LLMs via Alternating Optimization of LoRA
Shuangyi Chen, Yuanxin Guo, Yue Ju +3
Parameter-Efficient Fine-Tuning (PEFT) methods like Low-Rank Adaptation (LoRA) optimize federated training by reducing computational and communication costs. We propose RoLoRA, a f…
cs.LG2024
Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRA
Shuangyi Chen, Yue Ju, Hardik Dalal +2
Parameter-Efficient Fine-Tuning (PEFT) has risen as an innovative training strategy that updates only a select few model parameters, significantly lowering both computational and m…