Xi Cheng

Title: Innovations of Xi Cheng in Time-Series Forecasting

Introduction

Xi Cheng is an accomplished inventor based in Kirkland, WA (US). He has made significant contributions to the field of machine learning, particularly in time-series forecasting. With a total of 4 patents to his name, Cheng is recognized for his innovative approaches to predicting future data based on current time-series information.

Latest Patents

One of Xi Cheng's latest patents is titled "Machine Learning Super Large-Scale Time-Series Forecasting." This method involves executing operations on data processing hardware to forecast future data based on a set of current time-series data. The process includes receiving a forecasting query from a user, obtaining training data from the current time-series data, and training sub-models of a forecasting model. The model then forecasts future data and returns the results to the user.

Another notable patent is "Time Series Forecasting," which outlines a method for performing multiple time-series forecasts simultaneously. This method includes training a plurality of models for each forecast and determining which model best fits the respective data. The best-fitting model is then used to forecast future data, which is returned to the user.

Career Highlights

Xi Cheng is currently employed at Google Inc., where he continues to develop innovative solutions in machine learning and data analysis. His work has garnered attention for its practical applications in various industries, enhancing the accuracy and efficiency of time-series forecasting.

Collaborations

Cheng collaborates with talented individuals such as Jiashang Liu and Zichuan Ye, contributing to a dynamic team focused on advancing machine learning technologies.

Conclusion

Xi Cheng's contributions to time-series forecasting through his innovative patents demonstrate his expertise and commitment to advancing technology. His work at Google Inc. and collaborations with skilled colleagues further enhance the impact of his inventions in the field.