17 citations · 25 across the 6 of their papers we have counts for
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cs.LG2023★ 2 cited
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning
Yun-Hin Chan, Rui Zhou, Running Zhao +2
Federated learning (FL) inevitably confronts the challenge of system heterogeneity in practical scenarios. To enhance the capabilities of most model-homogeneous FL methods in handl…
cs.LG2023★ 1 cited
FedIN: Federated Intermediate Layers Learning for Model Heterogeneity
Yun-Hin Chan, Zhihan Jiang, Jing Deng +1
Federated learning (FL) facilitates edge devices to cooperatively train a global shared model while maintaining the training data locally and privately. However, a common assumptio…