Chi-yu Chang

Title: Chi-yu Chang and Federated Learning Innovation.

Introduction

Chi-yu Chang is an inventor based in Taichung, Taiwan. His patent work focuses on federated learning, distributed clustering, and methods for coordinating machine-learning models across participating nodes.

Latest Patents

Chang is associated with 1 patent: “Computer Implemented Multi-Layer Federated Learning Method Based on Distributed Clustering and Non-Transitory Computer Readable Medium Thereof.” The invention groups participating nodes with non-independent and identically distributed data into clusters according to feature-distribution similarity. It then updates each cluster’s local models using a federated learning algorithm and applies a multi-layer aggregation mechanism until the clustering results meet the required criteria. The described system also incorporates blockchain-based components, including model aggregation, an API, time-series synchronization, and IPFS. The patent presents this distributed-clustering approach as a way to improve learning performance.

Career Highlights

Chang is associated with Asia University. His patent reflects work on distributed machine learning and the coordination of models across data sources.

Collaborations

The supplied information identifies Zon-yin Shae and Kun-yi Chen as Chang’s coworkers.

Conclusion

Chi-yu Chang’s patent centers on combining distributed clustering with multi-layer federated learning to support model training across participating nodes.