FedSyn: Synthetic Data Generation using Federated Learning

Understand

As Deep Learning algorithms continue to evolve and become more sophisticated, they require massive datasets for model training and efficacy of models.

• Some of those data requirements can be met with the help of existing datasets within the organizations.
• Current Machine Learning practices can be leveraged to generate synthetic data from an existing dataset.
• Further, it is well established that diversity in generated synthetic data relies on (and is perhaps limited by) statistical properties of available dataset within a single organization or entity.