2 papers
cs.LG2024
Faster Adaptive Decentralized Learning Algorithms
Feihu Huang, Jianyu Zhao
Decentralized learning recently has received increasing attention in machine learning due to its advantages in implementation simplicity and system robustness, data privacy. Meanwh…
cs.LG2023
FedDA: Faster Framework of Local Adaptive Gradient Methods via Restarted Dual Averaging
Junyi Li, Feihu Huang, Heng Huang
Federated learning (FL) is an emerging learning paradigm to tackle massively distributed data. In Federated Learning, a set of clients jointly perform a machine learning task under…