Zonglin Di*

Federated Learning with Local Openset Noisy Labels

"Federated learning (FL) is a learning paradigm that allows the central server to learn from different data sources while keeping the data private locally. Without controlling and monitoring the local data collection process, the locally available training labels are likely noisy, i.e., the collecte…