3 papers
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…
cs.LG2022
Adaptive Learning for Service Monitoring Data
Farzana Anowar, Samira Sadaoui, Hardik Dalal
Service monitoring applications continuously produce data to monitor their availability. Hence, it is critical to classify incoming data in real-time and accurately. For this purpo…