3 papers
cs.LG2025
Benchmarking Federated Machine Unlearning methods for Tabular Data
Chenguang Xiao, Abhirup Ghosh, Han Wu +2
Machine unlearning, which enables a model to forget specific data upon request, is increasingly relevant in the era of privacy-centric machine learning, particularly within federat…
cs.LG2024
FedGA: Federated Learning with Gradient Alignment for Error Asymmetry Mitigation
Chenguang Xiao, Zheming Zuo, Shuo Wang
Federated learning (FL) triggers intra-client and inter-client class imbalance, with the latter compared to the former leading to biased client updates and thus deteriorating the d…
cs.LG2024
Rethinking the initialization of Momentum in Federated Learning with Heterogeneous Data
Chenguang Xiao, Shuo Wang
Data Heterogeneity is a major challenge of Federated Learning performance. Recently, momentum based optimization techniques have beed proved to be effective in mitigating the heter…