Patents by Inventor Parikshit Verma

Parikshit Verma 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).

  • MACHINE LEARNING MODEL FOR DYNAMICALLY BOOSTING ORDER DELIVERY TIME
    Publication number: 20240249238
    Abstract: A method or a system for using machine learning to dynamically boost order delivery time. The system receives an order associated with a delivery time and a compensation value. The system applies a machine-learning model to an order to predict an amount of lateness time that an order will be fulfilled late. The system then determines a lateness value based in part on the predicted amount of lateness time. The lateness value indicates a penalty caused by the predicted amount of lateness time. For each of a plurality of proposed boost amounts for the compensation value, the system determines an uplift, indicating a reduction of the lateness value caused by the boost amount. The system then selects a boost amount from the plurality of boost amounts based in part on the determined uplifts, causing the order to be accepted sooner to thereby boost order delivery time.
    Type: Application
    Filed: January 23, 2023
    Publication date: July 25, 2024
    Inventors: Konrad Gustav Miziolek, Parikshit Verma
  • Evaluation framework for anomaly detection using aggregated time-series signals
    Patent number: 12019616
    Abstract: Techniques are provided for evaluating one or more anomaly detection models using aggregated time-series signals.
    Type: Grant
    Filed: January 24, 2022
    Date of Patent: June 25, 2024
    Assignee: Dell Products L.P.
    Inventors: Saila Parthasarathy, Parikshit Verma, Oshry Ben-Harush, Joseph Standerfer, Te Ken
  • EVALUATION FRAMEWORK FOR ANOMALY DETECTION USING AGGREGATED TIME-SERIES SIGNALS
    Publication number: 20230237044
    Abstract: Techniques are provided for evaluating one or more anomaly detection models using aggregated time-series signals.
    Type: Application
    Filed: January 24, 2022
    Publication date: July 27, 2023
    Inventors: Saila Parthasarathy, Parikshit Verma, Oshry Ben-Harush, Joseph Standerfer, Te Ken