Implementation of Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- It is a decentralised learning framework that enables privacy preserving training of ML models for heterogeneous clients on practical networks.
- Wrote unit tests for various components of Envisedge - a deployment library for recommendation engines with Edge Computing. github
