Cross-Silo Heterogeneous Model Federated Multitask Learning

Understand

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 federated learning (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 study, we present a novel federated learning method CoFED based on unlabeled data pseudolabeling via a process known as cotraining.