Federated Local Causal Structure Learning Algorithm

Information Science, Computer Science, Artificial Intelligence, Medicine,
causal structure   federated learning   directed acyclic graph   privacy-preserving data   layer-wise strategy  

Intersection of Data Privacy and Causal Learning: Breakthrough in Federated Local Causal Structure Learning With the rapid development of big data and artificial intelligence, analyzing and inferring causal relationships while ensuring data privacy in sensitive fields such as healthcare and finance has become a key challenge for academia and indust...

Relation-Guided Versatile Regularization for Federated Semi-Supervised Learning

Information Science, Computer Science, Artificial Intelligence,
federated learning   semi-supervised learning   versatile regularization   relation-guided   model aggregation   data privacy   decentralized training  

Academic Background and Problem Statement With the increasing prominence of data privacy issues, Federated Learning (FL) has emerged as a decentralized machine learning paradigm, allowing multiple clients to collaboratively train a global model without sharing data, thereby protecting data privacy. However, existing FL methods typically assume that...

Model-Heterogeneous Semi-Supervised Federated Learning for Medical Image Segmentation

Model-Heterogeneous Semi-Supervised Federated Learning for Medical Image Segmentation

Information Science, Artificial Intelligence, Medicine, Medical Imaging,
medical image segmentation   federated learning   semi-supervised learning   knowledge distilling   privacy protection  

Model-Heterogeneous Semi-Supervised Federated Learning for Medical Image Segmentation Background Introduction Medical image segmentation plays a crucial role in clinical diagnosis as it helps doctors identify and analyze diseases. However, this task typically faces challenges such as sensitive data, privacy issues, and expensive annotation costs. W...