Yanqing Chen

Title: Yanqing Chen and Asynchronous Federated Learning

Introduction

Yanqing Chen is an inventor based in Sunnyvale, California. Her patent work addresses asynchronous training of federated learning models, a method designed to coordinate model updates across multiple institutional clients.

Latest Patents

Chen is associated with 1 patent: “System and Method for Asynchronous Multi-Aspect Weighted Federated Learning.” The invention describes a system with a master and multiple institutional clients. The master runs an aggregation thread and separate client-management threads. Each client-management thread initiates or continues local model training and sends training events to the aggregation thread. The aggregation thread updates the global model and returns aggregation events to the relevant client-management thread, enabling asynchronous coordination of training.

Career Highlights

Chen is associated with Beijing Wodong Tianjun Information Technology Co., Ltd. Her patent reflects work on distributed machine learning systems and the coordination of local and global model updates.

Collaborations

Chen’s listed coworkers include Huasong Shan and Tao Zeng.

Conclusion

Yanqing Chen’s patent focuses on asynchronous federated learning, coordinating institutional clients and a central aggregation process to train a shared model.