Patents by Inventor Xingxuan ZHOU

Xingxuan ZHOU has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20230410155
    Abstract: Deep neural network (DNN) models have been widely used for user-relevance content prediction. Presented herein is a new user-relevance framework, embodiments of which may be referred as Gating-Enhanced Multi-task Neural Networks (GemNN). In one or more, neural network-based multi-task learning model embodiments herein predict user engagement with content in a coarse-to-fine manner, which gradually reduces content candidates and allows parameter sharing from upstream tasks to downstream tasks to improve the training efficiency. Also, in one or more embodiments, a gating mechanism was introduced between embedding layers and multi-layer perceptions to learn feature interactions and control the information flow fed to MLP layers. Tested embodiments demonstrated considerable improvements over prior approaches.
    Type: Application
    Filed: July 7, 2021
    Publication date: December 21, 2023
    Applicants: Baidu USA LLC, Baidu.com Times Technology (Beijing) Co., Ltd.
    Inventors: Hongliang FEI, Jingyuan ZHANG, Xingxuan ZHOU, Junhao ZHAO, Banghu YIN, Ping LI