San Jose, CA, United States of America

William Yau


Average Co-Inventor Count = 13.0

ph-index = 1


Company Filing History:


Years Active: 2023-2024

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2 patents (USPTO):Explore Patents

Title: The Innovative Contributions of William Yau

Introduction

William Yau is an accomplished inventor based in San Jose, California. He has made significant contributions to the field of technology, particularly in the area of content item analysis. With a total of two patents to his name, Yau's work focuses on enhancing the way hair patterns are determined and filtered in various content items.

Latest Patents

Yau's latest patents revolve around systems and methods for hair pattern determination and filtering. These patents describe innovative approaches to identify hair patterns presented in content items. The determined hair patterns can be associated with the content items to facilitate indexing and filtering based on these patterns. In exemplary implementations, a corpus of content items is linked to an embedding vector that includes a binary representation of the content item. The embedding vectors associated with each content item serve as inputs to a trained machine learning model. This model processes the embedding vectors to determine one or more hair patterns presented in each content item, eliminating the need for image pre-processing prior to the determination of the hair patterns.

Career Highlights

William Yau is currently employed at Pinterest, Inc., where he applies his expertise in machine learning and content analysis. His innovative work has contributed to the advancement of technologies that enhance user experience on the platform.

Collaborations

Yau collaborates with talented individuals such as Nadia Fawaz and Anh Tuong Ta, who share his passion for innovation and technology.

Conclusion

William Yau's contributions to the field of content item analysis through his patents demonstrate his commitment to innovation. His work not only enhances the understanding of hair patterns in content but also showcases the potential of machine learning in practical applications.

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