PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records

arXiv:2112.05321v2 Announce Type: replace
Abstract: Federated machine learning is a versatile and flexible tool to utilize distributed data from different sources, especially when communication technology develops rapidly and an unprecedented amount of data could be collected on mobile devices nowadays. Federated learning method exploits not only the data but the computational power of all devices in the network to achieve more efficient model training. Nevertheless, while most traditional federated learning methods work well for homogeneous data and tasks, adapting the …

abstract applications arxiv communication cs.lg data devices distributed distributed data exploits federated learning machine machine learning medical medical records meta mobile mobile devices records tasks technology tool type world