most citedDFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning

7 citations · 10 across the 6 of their papers we have counts for

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cs.CV2023★ 7 cited

DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning

Kangyang Luo, Shuai Wang, Yexuan Fu +3

Federated Learning (FL) is a privacy-constrained decentralized machine learning paradigm in which clients enable collaborative training without compromising private data. However,…

cs.CV2023★ 1 cited

GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting

Kangyang Luo, Xiang Li, Yunshi Lan +1

Federated Learning (FL) has emerged as a de facto machine learning area and received rapid increasing research interests from the community. However, catastrophic forgetting caused…