Tianjian Chen

Title: Innovations of Tianjian Chen in Federation Learning

Introduction

Tianjian Chen is a prominent inventor based in Shenzhen, China. He has made significant contributions to the field of federation learning, particularly through his innovative patent. His work focuses on enhancing model parameter training methods, which are crucial for the development of advanced machine learning systems.

Latest Patents

Tianjian Chen holds a patent for a "Model parameter training method, terminal, and system based on federation learning." This patent outlines a method that includes determining a feature intersection of samples from different terminals, training a mapping model, and utilizing encryption to enhance the training process. The method aims to improve the efficiency and accuracy of model training in distributed systems.

Career Highlights

Tianjian Chen is currently employed at WeBank Co., Ltd., where he applies his expertise in machine learning and federation learning. His innovative approach has positioned him as a key figure in the development of cutting-edge technologies in the banking and finance sectors.

Collaborations

Tianjian collaborates with notable colleagues such as Yang Liu and Yan Kang. Their combined efforts contribute to the advancement of technologies that leverage federation learning for improved data processing and analysis.

Conclusion

Tianjian Chen's contributions to federation learning exemplify the innovative spirit of modern inventors. His work not only enhances the capabilities of machine learning systems but also paves the way for future advancements in the field.