Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity.
Bo LiYasin EsfandiariMikkel N. SchmidtTommy S. AlstrømSebastian U. StichPublished in: CoRR (2023)
Keyphrases
- synthetic data
- data sets
- data sources
- learning systems
- data collection
- database
- real world
- statistical analysis
- reinforcement learning
- prior knowledge
- online learning
- supervised learning
- data mining techniques
- learned models
- mri data
- human experts
- input data
- training data
- database systems
- learning algorithm
- end users
- digital libraries
- high quality
- sensor data
- learning tasks
- decision trees
- noisy data
- synthetic datasets
- distributed data
- neural network
- previously learned