2 papers
cs.CV2023
FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning
Peiran Xu, Zeyu Wang, Jieru Mei +4
Federated learning (FL) is an emerging paradigm in machine learning, where a shared model is collaboratively learned using data from multiple devices to mitigate the risk of data l…
cs.SI2021
Null Model-Based Data Augmentation for Graph Classification
Qi Xuan, Zeyu Wang, Jinhuan Wang +3
In network science, the null model is typically used to generate a series of graphs based on randomization as a term of comparison to verify whether a network in question displays…