Showing cs.LGShow all
3 papers · 1 filter
cs.LG2025
Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission
Faranaksadat Solat, Joohyung Lee, Mohamed Seif +2
Hybrid Language Models (HLMs) combine the low-latency efficiency of Small Language Models (SLMs) on edge devices with the high accuracy of Large Language Models (LLMs) on centraliz…
cs.LG2024
Towards Communication-efficient Federated Learning via Sparse and Aligned Adaptive Optimization
Xiumei Deng, Jun Li, Kang Wei +6
Adaptive moment estimation (Adam), as a Stochastic Gradient Descent (SGD) variant, has gained widespread popularity in federated learning (FL) due to its fast convergence. However,…
cs.LG2023
Exploring Federated Unlearning: Review, Comparison, and Insights
Yang Zhao, Jiaxi Yang, Yiling Tao +4
The increasing demand for privacy-preserving machine learning has spurred interest in federated unlearning, which enables the selective removal of data from models trained in feder…