Exploration Across Small Silos: Federated Few-Shot Learning on Network Edge

Federated Learning (FL) has been drawing significant attention from both academia and industry working on distributed machine learning. In practice, learning over mutually isolated datasets residing at the network edge, also known as silos, FL clients can suffer from a lack of samples, due to many reasons (e.g., expensive annotation), and this has potentially significant negative impact on FL perf...