Patents by Inventor Arjun Karat

Arjun Karat 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).

  • Applying scoring systems using an auto-machine learning classification approach
    Patent number: 12210937
    Abstract: A method of improving usability and transparency of machine-learning aspects of applications providing various types of services is disclosed. Based on a request submitted through an administrative user interface, a data readiness check is performed on underlying data associated with the application. Based on a successful completion of the data readiness check, a configuration file is retrieved from an application server. The configuration file specifies a plurality of keys for generating a machine-learned model for the application. The machine-learned model is trained based on the plurality of keys specified in the configuration file. The machine-learned model is selected from a plurality of machine-learned models based on dry runs of the each of the plurality of models. The machine-learned model is activated with respect to the application. Scores are identified from the underlying data items based on the selected machine-learned model.
    Type: Grant
    Filed: November 16, 2018
    Date of Patent: January 28, 2025
    Assignee: SAP SE
    Inventors: Karthik S J, Amy He, Prajesh K, Georg Glantschnig, Riya Thosar, Arjun Karat, Yann Le Biannic, Jing Ye, Subhobrata Dey, Prerna Makanawala, Xiaoqing He
  • APPLYING SCORING SYSTEMS USING AN AUTO-MACHINE LEARNING CLASSIFICATION APPROACH
    Publication number: 20200159690
    Abstract: A method of improving usability and transparency of machine-learning aspects of applications providing various types of services is disclosed. Based on a request submitted through an administrative user interface, a data readiness check is performed on underlying data associated with the application. Based on a successful completion of the data readiness check, a configuration file is retrieved from an application server. The configuration file specifies a plurality of keys for generating a machine-learned model for the application. The machine-learned model is trained based on the plurality of keys specified in the configuration file. The machine-learned model is selected from a plurality of machine-learned models based on dry runs of the each of the plurality of models. The machine-learned model is activated with respect to the application. Scores are identified from the underlying data items based on the selected machine-learned model.
    Type: Application
    Filed: November 16, 2018
    Publication date: May 21, 2020
    Inventors: Karthik S. J, Amy He, Prajesh K, Georg Glantschnig, Riya Thosar, Arjun Karat, Yann Le Biannic, Jing Ye, Subhobrata Dey, Prerna Makanawala, Xiaoqing He