Patents by Inventor Parul Awasthy

Parul Awasthy 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).

  • Predictive data and model selection for transfer learning in natural language processing
    Patent number: 11934922
    Abstract: A computer system, product, and method are provided. The computer system includes an artificial intelligence (AI) platform operatively coupled to a processor. The AI platform includes tools in the form of a machine learning model (MLM) manager, a metric manager, and a training manager. The MLM manager accesses a plurality of pre-trained source MLMs, and inputs a plurality of data objects of a test dataset into each of the source MLMs. The test dataset includes the plurality of data objects associated with respective labels. For each source MLM, associated labels are generated from the inputted data objects and a similarity metric is calculated. The MLM manager selects a base MLM to be used for transfer learning from the plurality of source MLMs based upon the calculated similarity metric. The training manager trains the selected base MLM with a target dataset for the target domain.
    Type: Grant
    Filed: October 9, 2020
    Date of Patent: March 19, 2024
    Assignee: International Business Machines Corporation
    Inventors: Parul Awasthy, Bishwaranjan Bhattacharjee, John Ronald Kender, Radu Florian, Hui Wan
  • Predictive Data and Model Selection for Transfer Learning in Natural Language Processing
    Publication number: 20220114473
    Abstract: A computer system, product, and method are provided. The computer system includes an artificial intelligence (AI) platform operatively coupled to a processor. The AI platform includes tools in the form of a machine learning model (MLM) manager, a metric manager, and a training manager. The MLM manager accesses a plurality of pre-trained source MLMs, and inputs a plurality of data objects of a test dataset into each of the source MLMs. The test dataset includes the plurality of data objects associated with respective labels. For each source MLM, associated labels are generated from the inputted data objects and a similarity metric is calculated. The MLM manager selects a base MLM to be used for transfer learning from the plurality of source MLMs based upon the calculated similarity metric. The training manager trains the selected base MLM with a target dataset for the target domain.
    Type: Application
    Filed: October 9, 2020
    Publication date: April 14, 2022
    Applicant: International Business Machines Corporation
    Inventors: Parul Awasthy, Bishwaranjan Bhattacharjee, John Ronald Kender, Radu Florian, Hui Wan