Guile Wu

Title: Guile Wu - Innovator in De-centralised Learning for Re-identification

Introduction

Guile Wu is a notable inventor based in London, GB. He has made significant contributions to the field of machine learning, particularly in the area of re-identification through his innovative patent. His work focuses on optimizing domain-generalisable models, which are crucial for identifying targets within a set of candidate images.

Latest Patents

Guile Wu holds a patent titled "De-centralised learning for re-identification." This patent describes a method for generating an optimized domain-generalisable model for the re-identification of a target in a set of candidate images. The method involves optimizing a local feature embedding model for domain-specific feature representation at each client. It also includes receiving information on changes to the local feature embedding model at each respective client, updating a global feature embedding model based on these changes, and mapping updates back to the local models until convergence criteria are met.

Career Highlights

Guile Wu is currently employed at Veritone, Inc., where he applies his expertise in machine learning and artificial intelligence. His work at Veritone focuses on developing advanced technologies that enhance the capabilities of AI systems. His innovative approach has positioned him as a key player in the field.

Collaborations

Guile Wu collaborates with Shaogang Gong, a fellow expert in the field. Together, they work on projects that push the boundaries of machine learning and its applications in various industries.

Conclusion

Guile Wu's contributions to the field of de-centralised learning and re-identification demonstrate his commitment to advancing technology. His innovative patent and work at Veritone, Inc. highlight his role as a leading inventor in the industry.