Patents by Inventor Hanjun Xian

Hanjun Xian 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).

  • Training and operation of computational models
    Patent number: 10474950
    Abstract: A processing unit can acquire datasets from respective data sources, each having a respective unique data domain. The processing unit can determine values of a plurality of features based on the plurality of datasets. The processing unit can modify input-specific parameters or history parameters of a computational model based on the values of the features. In some examples, the processing unit can determine an estimated value of a target feature based at least in part on the modified computational model and values of one or more reference features. In some examples, the computational model can include neural networks for several input sets. An output layer of at least one of the neural networks can be connected to the respective hidden layer(s) of one or more other(s) of the neural networks. In some examples, the neural networks can be operated to provide transformed feature value(s) for respective times.
    Type: Grant
    Filed: June 29, 2015
    Date of Patent: November 12, 2019
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Xiaodong He, Jianshu Chen, Brendan W L Clement, Li Deng, Jianfeng Gao, Bochen Jin, Prabhdeep Singh, Sandeep P. Solanki, LuMing Wang, Hanjun Xian, Yilei Zhang, Mingyang Zhao, Zijian Zheng
  • TRAINING AND OPERATION OF COMPUTATIONAL MODELS
    Publication number: 20160379112
    Abstract: A processing unit can acquire datasets from respective data sources, each having a respective unique data domain. The processing unit can determine values of a plurality of features based on the plurality of datasets. The processing unit can modify input-specific parameters or history parameters of a computational model based on the values of the features. In some examples, the processing unit can determine an estimated value of a target feature based at least in part on the modified computational model and values of one or more reference features. In some examples, the computational model can include neural networks for several input sets. An output layer of at least one of the neural networks can be connected to the respective hidden layer(s) of one or more other(s) of the neural networks. In some examples, the neural networks can be operated to provide transformed feature value(s) for respective times.
    Type: Application
    Filed: June 29, 2015
    Publication date: December 29, 2016
    Inventors: Xiaodong He, Jianshu Chen, Brendan WL Clement, Li Deng, Jianfeng Gao, Bochen Jin, Prabhdeep Singh, Sandeep P. Solanki, LuMing Wang, Hanjun Xian, Yilei Zhang, Mingyang Zhao, Zijian Zheng