Patents by Inventor Dingxiang Hu

Dingxiang Hu 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).

  • Patent number: 11107109
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for personalizing offers are provided. One of the methods includes: collecting response data comprising one or more offers made to each of a plurality of users of a platform and one or more corresponding responses, wherein the one or more offers are from a group of offer choices; creating a training dataset comprising the collected response data and one or more features associated with each of the plurality of users; training a machine learning model using the training dataset, wherein the trained machine learning model is configured to predict the plurality of users' responses to future offers; obtaining a plurality of projected profits for the platform using the trained machine learning model, wherein each of the plurality of projected profits corresponds to making one of the group of the predetermined offers to one of the plurality of users.
    Type: Grant
    Filed: December 29, 2020
    Date of Patent: August 31, 2021
    Assignee: ALIPAY (HANGZHOU) INFORMATION TECHNOLOGY CO., LTD.
    Inventors: Feng Qi, Jia Yan, Zhigang Hua, Dingxiang Hu, Yingping Cao, Shuang Yang
  • Publication number: 20210118004
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for personalizing offers are provided. One of the methods includes: collecting response data comprising one or more offers made to each of a plurality of users of a platform and one or more corresponding responses, wherein the one or more offers are from a group of offer choices; creating a training dataset comprising the collected response data and one or more features associated with each of the plurality of users; training a machine learning model using the training dataset, wherein the trained machine learning model is configured to predict the plurality of users' responses to future offers; obtaining a plurality of projected profits for the platform using the trained machine learning model, wherein each of the plurality of projected profits corresponds to making one of the group of the predetermined offers to one of the plurality of users.
    Type: Application
    Filed: December 29, 2020
    Publication date: April 22, 2021
    Inventors: Feng QI, Jia YAN, Zhigang HUA, Dingxiang HU, Yingping CAO, Shuang YANG
  • Patent number: 9352758
    Abstract: The present invention relates to a flexible direct-drive bogie and implements a flexible frame by using a flexible cross beam, so as to make it easy for left and right side-frames to nod relatively to adapt to a larger twist of a track. As the frame is flexible, a primary suspension of the present invention is simplified to a thin layer of rubber pad, so that the production cost is reduced. Flexible drive devices enable flexible suspension of a permanent magnetic motor, and at the same time, can transmit torque, improve transmission efficiency, and reduce a weight of a transmission mechanism.
    Type: Grant
    Filed: July 17, 2012
    Date of Patent: May 31, 2016
    Assignee: CSR NANJING PUZHEN CO., LTD.
    Inventors: Yongping Chu, Yongming Tang, Zunwei Feng, Dingxiang Hu, Rui Zhou
  • Publication number: 20140261061
    Abstract: The present invention relates to a flexible direct-drive bogie and implements a flexible frame by using a flexible cross beam, so as to make it easy for left and right side-frames to nod relatively to adapt to a larger twist of a track. As the frame is flexible, a primary suspension of the present invention is simplified to a thin layer of rubber pad, so that the production cost is reduced.
    Type: Application
    Filed: July 17, 2012
    Publication date: September 18, 2014
    Inventors: Yongping Chu, Yongming Tang, Zunwei Feng, Dingxiang Hu, Rui Zhou