Jingxian Liao

Title: Innovations of Jingxian Liao

Introduction

Jingxian Liao is a notable inventor based in San Jose, CA, who has made significant contributions to the field of machine learning. With a total of 2 patents, Liao's work focuses on enhancing predictive models and data augmentation techniques.

Latest Patents

Liao's latest patents include a method for generating estimates by combining unsupervised and supervised machine learning. This method involves obtaining a cluster of reference entities and calculating distances between features of a target entity and those of the subset. By selecting peer entities based on these distances, Liao's method generates an estimated value of a metric, applying a machine learning model trained on labeled data. Another patent focuses on a method of machine learning training for data augmentation. This method trains an untrained prediction model using accepted data with known labels, generating predicted labels for unknown data and confidence scores for these predictions. The process includes selecting a subset of unknown data based on confidence scores and retraining the prediction model with confident labels.

Career Highlights

Jingxian Liao is currently employed at Intuit, Inc., where he continues to innovate in the realm of machine learning. His work has implications for various applications, enhancing the accuracy and efficiency of predictive analytics.

Collaborations

Liao collaborates with talented individuals such as Anthony Hiotong Wong Lei and Zhicheng Xue, contributing to a dynamic work environment that fosters innovation.

Conclusion

Jingxian Liao's contributions to machine learning through his patents and work at Intuit, Inc. highlight his role as a forward-thinking inventor. His innovative methods are paving the way for advancements in predictive modeling and data analysis.