2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2025★ 2 cited
A Two-Timescale Approach for Wireless Federated Learning with Parameter Freezing and Power Control
Jinhao Ouyang, Yuan Liu, Hang Liu
Federated learning (FL) enables distributed devices to train a shared machine learning (ML) model collaboratively while protecting their data privacy. However, the resource-limited…
math.NA2024
FCNCP: A Coupled Nonnegative CANDECOMP/PARAFAC Decomposition Based on Federated Learning
Yukai Cai, Hang Liu, Xiulin Wang +4
In the field of brain science, data sharing across servers is becoming increasingly challenging due to issues such as industry competition, privacy security, and administrative pro…
cs.LG2023
Tango: rethinking quantization for graph neural network training on GPUs
Shiyang Chen, Da Zheng, Caiwen Ding +3
Graph Neural Networks (GNNs) are becoming increasingly popular due to their superior performance in critical graph-related tasks. While quantization is widely used to accelerate GN…