Cross-Silo Heterogeneous Model Federated Multitask Learning. (arXiv:2202.08603v3 [cs.LG] UPDATED)

Federated learning (FL) is a machine learning technique that enables
participants to collaboratively train high-quality models without exchanging
their private data. Participants utilizing cross-silo FL (CS-FL) settings are
independent organizations with different task needs, and they are concerned not
only with data privacy but also with independently training their unique models
due to intellectual property considerations. Most existing FL methods are
incapable of satisfying the above scenarios. In this paper, we propose a FL
method based on the pseudolabeling of …

arxiv learning lg multitask learning