Jingzhao Zhang

Title: Innovations of Jingzhao Zhang in Adaptive Optimization

Introduction

Jingzhao Zhang is an accomplished inventor based in Cambridge, MA (US). He has made significant contributions to the field of adaptive optimization, particularly in the context of machine learning. His innovative approach has led to the development of techniques that enhance the convergence properties of optimization algorithms.

Latest Patents

Jingzhao Zhang holds a patent for "Fast Adaptive Optimization." This patent describes systems and methods that perform adaptive optimization with improved convergence properties. The techniques outlined in the patent are particularly useful in various optimization scenarios, including the training of machine-learned models such as neural networks. The system employs an adaptive per coordinate clipping threshold to clip the current first moment of the coordinate, resulting in a current update value that enables faster convergence for machine-learned models, especially when the noise in the stochastic gradients is heavy-tailed. He has 1 patent to his name.

Career Highlights

Jingzhao Zhang is currently associated with Google Inc., where he continues to work on innovative solutions in the field of machine learning and optimization. His work has garnered attention for its practical applications and effectiveness in improving algorithm performance.

Collaborations

Jingzhao has collaborated with notable colleagues, including Seungyeon Kim and Andreas Veit. Their combined expertise contributes to the advancement of research and development in adaptive optimization techniques.

Conclusion

Jingzhao Zhang's contributions to adaptive optimization represent a significant advancement in the field of machine learning. His innovative patent and ongoing work at Google Inc. highlight his role as a leading inventor in this area.