Patents by Inventor Raghvendra Kumar YADAV

Raghvendra Kumar YADAV 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 techniques for determining predicted similarity scores for input sequences
    Patent number: 11948378
    Abstract: Systems and methods for dynamically generating a predicted similarity score for a pair of input sequences. A predicted similarity score for a pair of input sequences is determined based at least in part on at least one of a token-level similarity probability score for the pair of input sequences, a target region match indication for the pair of input sequences, a fuzzy match score for the pair of input sequences, a character-level match score for the pair of input sequences, one or more similarity ratio occurrence indicators for the pair of input sequences, and a harmonic mean score of the fuzzy match score for the pair of input sequences and the token-level similarity probability score for the pair of input sequences.
    Type: Grant
    Filed: December 23, 2021
    Date of Patent: April 2, 2024
    Assignee: UnitedHealth Group Incorporated
    Inventors: Subhodeep Dey, Brad Booher, Edward Sverdlin, Reshma S. Ombase, Raghvendra Kumar Yadav
  • MACHINE LEARNING TECHNIQUES FOR DETERMINING PREDICTED SIMILARITY SCORES FOR INPUT SEQUENCES
    Publication number: 20230206666
    Abstract: Various embodiments of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for dynamically generating a predicted similarity score for a pair of input sequences. According to one aspect, a predicted similarity score for a pair of input sequences is determined based at least in part on at least one of a token-level similarity probability score for the pair of input sequences, a target region match indication for the pair of input sequences, a fuzzy match score for the pair of input sequences, a character-level match score for the pair of input sequences, one or more similarity ratio occurrence indicators for the pair of input sequences, and a harmonic mean score of the fuzzy match score for the pair of input sequences and the token-level similarity probability score for the pair of input sequences.
    Type: Application
    Filed: December 23, 2021
    Publication date: June 29, 2023
    Inventors: Subhodeep DEY, Brad BOOHER, Edward SVERDLIN, Reshma S. OMBASE, Raghvendra Kumar YADAV
  • MACHINE LEARNING TECHNIQUES FOR HYBRID TEMPORAL-UTILITY CLASSIFICATION DETERMINATIONS
    Publication number: 20230153681
    Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis operations by dynamically determining a hybrid temporal-utility classification for a predictive entity. The hybrid temporal-utility classification for the predictive entity may be determined based at least in part on outputs from a temporal score generation machine learning model and a utility score generation machine learning model.
    Type: Application
    Filed: November 16, 2021
    Publication date: May 18, 2023
    Inventors: Subhadradevi KYANAM, Apoorva NIGAM, Vaishnavi V. G, Raghvendra Kumar YADAV, Biswajit BHATTACHARJEE, Anders WOLF