Learn the Global Prompt in the Low-Rank Tensor Space for Heterogeneous Federated Learning

Academic Background With the increasing complexity of artificial intelligence (AI) models and the growing demand for data privacy protection, Federated Learning (FL) has emerged as a hot research topic as a distributed machine learning paradigm. Federated Learning allows multiple clients to collaboratively train a global model without sharing local...

Federated Learning Using Model Projection for Multi-Center Disease Diagnosis with Non-IID Data

Federated Learning Using Model Projection for Multi-Center Disease Diagnosis with Non-IID Data

Federated Learning Using Model Projection for Multi-Center Disease Diagnosis Background Introduction With the rapid development of medical imaging technology, research on automated diagnostic methods has shown good performance on single-center datasets. However, these methods often find it difficult to generalize to data from other healthcare facil...