Kunbo Zhang

Title: Kunbo Zhang: Innovator in Federated Learning

Introduction

Kunbo Zhang is a prominent inventor based in Beijing, China. He has made significant contributions to the field of federated learning, focusing on methods that enhance data privacy and model performance. With a total of 2 patents, his work is paving the way for advancements in machine learning technologies.

Latest Patents

Zhang's latest patents include a "Disentangled Personalized Federated Learning Method via Consensus Representation Extraction and Diversity Propagation." This innovative method involves receiving local consensus representation extraction models and unique representation extraction models from other nodes. It allows the current node to extract representations of its data and calculate mutual information to determine the similarity of data distributions between nodes.

Another notable patent is the "Method for Updating a Node Model that Resists Discrimination Propagation in Federated Learning." This method focuses on updating a node model to resist discrimination propagation by calculating various parameters, including the mean value of class feature distributions and a distribution weighted aggregation model. It aims to enhance the robustness of federated learning models against biases.

Career Highlights

Kunbo Zhang is affiliated with the Chinese Academy of Sciences, where he conducts research and develops innovative solutions in the realm of artificial intelligence and machine learning. His work is recognized for its potential to transform how data is processed and utilized in various applications.

Collaborations

Zhang collaborates with esteemed colleagues, including Zhenan Sun and Yunlong Wang. Their combined expertise contributes to the advancement of research in federated learning and related fields.

Conclusion

Kunbo Zhang's contributions to federated learning exemplify the innovative spirit of modern inventors. His patents reflect a commitment to enhancing data privacy and model efficiency, marking him as a key figure in the evolution of machine learning technologies.