Yanping Huang

Title: Yanping Huang: Innovator in Neural Network Architecture

Introduction

Yanping Huang is a prominent inventor based in Mountain View, CA, known for her significant contributions to the field of machine learning and neural networks. With a total of six patents to her name, she has made remarkable strides in optimizing neural network architectures.

Latest Patents

One of her latest patents is titled "Regularized Neural Network Architecture Search." This patent describes a method for receiving training data to train a neural network (NN) for machine learning tasks. It outlines a process for determining an optimized NN architecture by maintaining population data for candidate architectures and performing operations using worker computing units to generate new candidate architectures. Another notable patent is "Training of Large Neural Networks," which encompasses methods, systems, and apparatus for training neural networks to perform various machine learning tasks, including configurations as generative neural networks.

Career Highlights

Yanping Huang is currently employed at Google Inc., where she continues to push the boundaries of technology in her field. Her work has been instrumental in advancing the capabilities of neural networks, making them more efficient and effective for various applications.

Collaborations

Throughout her career, Yanping has collaborated with notable colleagues, including Alok Aggarwal and Quoc V Le. These collaborations have further enriched her research and development efforts in machine learning.

Conclusion

Yanping Huang's innovative work in neural network architecture and her contributions to machine learning exemplify her status as a leading inventor in the technology sector. Her patents reflect her commitment to advancing the field and improving the efficiency of neural networks.