Patents by Inventor Kailun YAN

Kailun YAN 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: 11949797
    Abstract: Disclosed are a neural network model update method and device, and a computer storage medium. The method includes: randomly generating a preset number of sub-neural network models as nodes in a blockchain; using a ring signature to share a local data set in the blockchain, and uniformly dividing a data set in the blockchain to generate a training set and a test set; training each node through the training set to generate a trained model, packaging the trained model as a model transaction and sharing the model transaction in the blockchain; using the test set selected by voting to test the model transaction and generating a test result; when the test result is greater than a benchmark evaluation, taking the sub-neural network model corresponding to the test result as a valid vote; and voting a previous block corresponding to the valid vote, selecting a consistent block, and updating all nodes.
    Type: Grant
    Filed: September 14, 2021
    Date of Patent: April 2, 2024
    Assignee: Jinan University
    Inventors: Jilian Zhang, Kailun Yan, Yongdong Wu, Jian Weng
  • Publication number: 20220209963
    Abstract: Disclosed are a neural network model update method and device, and a computer storage medium. The method includes: randomly generating a preset number of sub-neural network models as nodes in a blockchain; using a ring signature to share a local data set in the blockchain, and uniformly dividing a data set in the blockchain to generate a training set and a test set; training each node through the training set to generate a trained model, packaging the trained model as a model transaction and sharing the model transaction in the blockchain; using the test set selected by voting to test the model transaction and generating a test result; when the test result is greater than a benchmark evaluation, taking the sub-neural network model corresponding to the test result as a valid vote; and voting a previous block corresponding to the valid vote, selecting a consistent block, and updating all nodes.
    Type: Application
    Filed: September 14, 2021
    Publication date: June 30, 2022
    Inventors: Jilian ZHANG, Kailun YAN, Yongdong WU, Jian WENG