Patents by Inventor Thomas Ryan Hoens

Thomas Ryan Hoens 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: 10685281
    Abstract: Systems and methods for providing a predictive framework are provided. The predictive framework comprises plural neural layers of adaptable, executable neurons. Neurons accept one or more input signals and produce an output signal that may be used by an upper-level neural layer. Input signals are received by an encoding neural layer, where there is a 1:1 correspondence between an input signal and an encoding neuron. Input signals for a set of data are received at the encoding layer and processed successively by the plurality of neural layers. An objective function utilizes the output signals of the topmost neural layer to generate predictive results for the data set according to an objective. In one embodiment, the objective is to determine the likelihood of user interaction with regard to a specific item of content in a set of search results, or the likelihood of user interaction with regard to any item of content in a set of search results.
    Type: Grant
    Filed: August 2, 2016
    Date of Patent: June 16, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Ying Shan, Thomas Ryan Hoens, Jian Jiao, Haijing Wang, Dong Yu, JC Mao
  • Publication number: 20170236056
    Abstract: Systems and methods for providing a predictive framework are provided. The predictive framework comprises plural neural layers of adaptable, executable neurons. Neurons accept one or more input signals and produce an output signal that may be used by an upper-level neural layer. Input signals are received by an encoding neural layer, where there is a 1:1 correspondence between an input signal and an encoding neuron. Input signals for a set of data are received at the encoding layer and processed successively by the plurality of neural layers. An objective function utilizes the output signals of the topmost neural layer to generate predictive results for the data set according to an objective. In one embodiment, the objective is to determine the likelihood of user interaction with regard to a specific item of content in a set of search results, or the likelihood of user interaction with regard to any item of content in a set of search results.
    Type: Application
    Filed: August 2, 2016
    Publication date: August 17, 2017
    Inventors: Ying Shan, Thomas Ryan Hoens, Jian Jiao, Haijing Wang, Dong Yu, JC Mao