On the Convergence of Cyclic Hierarchical Federated Learning with Heterogeneous Data

An official website of the United States government Here's how you know

Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Attention:

NSF PAR will be unavailable due to scheduled facility maintenance July 10th, 5 PM EDT through July 13th. We apologize for any inconvenience.

This content will become publicly available on June 26, 2027

On the Convergence of Cyclic Hierarchical Federated Learning with Heterogeneous Data

Publisher / Repository:: International Joint Conference on Neural Networks (IJCNN) 2026