Partial Federated Learning (PartialFL) addresses data heterogeneity in federated learning by allowing some data modalities to be shared with the server, leading to improved model performance.
Partial Federated Learning introduces a new algorithm, PartialFL, to train machine learning models with distributed data modalities, improving model performance and addressing data heterogeneity challenges.