7 citations · 8 across the 3 of their papers we have counts for
3 papers
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.DC2023
Decentralized Local Updates with Dual-Slow Estimation and Momentum-based Variance-Reduction for Non-Convex Optimization
Kangyang Luo, Kunkun Zhang, Shengbo Zhang +2
Decentralized learning (DL) has recently employed local updates to reduce the communication cost for general non-convex optimization problems. Specifically, local updates require e…
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…