2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 2 cited
On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning
Hanhan Zhou, Tian Lan, Guru Venkataramani +1
One of the biggest challenges in Federated Learning (FL) is that client devices often have drastically different computation and communication resources for local updates. To this…
cs.DC2021★ 1 cited
Communication Efficient Federated Learning with Adaptive Quantization
Yuzhu Mao, Zihao Zhao, Guangfeng Yan +4
Federated learning (FL) has attracted tremendous attentions in recent years due to its privacy preserving measures and great potentials in some distributed but privacy-sensitive ap…