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20232026
most citedFLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations

4 citations · 12 across the 28 of their papers we have counts for

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cs.LG2023★ 1 cited

FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent

Ziyao Wang, Jianyu Wang, Ang Li

The theoretical landscape of federated learning (FL) undergoes rapid evolution, but its practical application encounters a series of intricate challenges, and hyperparameter optimi…

cs.LG2023

FedNAR: Federated Optimization with Normalized Annealing Regularization

Junbo Li, Ang Li, Chong Tian +3

Weight decay is a standard technique to improve generalization performance in modern deep neural network optimization, and is also widely adopted in federated learning (FL) to prev…