Patents by Inventor Dhruv Chaudhari

Dhruv Chaudhari 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).

  • AUTOMATED TRAINING AND SELECTION OF MODELS FOR DOCUMENT ANALYSIS
    Publication number: 20220019943
    Abstract: Embodiments are directed to a machine learning engine that determines training documents and validation documents from a plurality of documents. The machine learning engine may determine attributes associated with the documents. In response to receiving a request to predict attribute values of a selected document the machine learning engine may train a plurality of ML models to predict the attribute values based on the training documents and the attributes and associate the trained ML models with an accuracy score. The machine learning engine may determine candidate ML models from the trained ML models based on the training accuracy scores. The machine learning engine may evaluate and rank the candidate ML models based on the request and the validation documents. The machine learning engine may generate confirmed ML models based on the ranked candidate ML models such that the confirmed ML models may answer the request.
    Type: Application
    Filed: February 26, 2021
    Publication date: January 20, 2022
    Inventors: Dhruv Chaudhari, Harshil Shah, Amitabh Jain, Monish Mangalkumar Darda
  • Automated training and selection of models for document analysis
    Patent number: 10936974
    Abstract: Embodiments are directed to a machine learning engine that determines training documents and validation documents from a plurality of documents. The machine learning engine may determine attributes associated with the documents. In response to receiving a request to predict attribute values of a selected document the machine learning engine may train a plurality of ML models to predict the attribute values based on the training documents and the attributes and associate the trained ML models with an accuracy score. The machine learning engine may determine candidate ML models from the trained ML models based on the training accuracy scores. The machine learning engine may evaluate and rank the candidate ML models based on the request and the validation documents. The machine learning engine may generate confirmed ML models based on the ranked candidate ML models such that the confirmed ML models may answer the request.
    Type: Grant
    Filed: December 24, 2018
    Date of Patent: March 2, 2021
    Assignee: Icertis, Inc.
    Inventors: Dhruv Chaudhari, Harshil Shah, Amitabh Jain, Monish Mangalkumar Darda
  • AUTOMATED TRAINING AND SELECTION OF MODELS FOR DOCUMENT ANALYSIS
    Publication number: 20200202256
    Abstract: Embodiments are directed to a machine learning engine that determines training documents and validation documents from a plurality of documents. The machine learning engine may determine attributes associated with the documents. In response to receiving a request to predict attribute values of a selected document the machine learning engine may train a plurality of ML models to predict the attribute values based on the training documents and the attributes and associate the trained ML models with an accuracy score. The machine learning engine may determine candidate ML models from the trained ML models based on the training accuracy scores. The machine learning engine may evaluate and rank the candidate ML models based on the request and the validation documents. The machine learning engine may generate confirmed ML models based on the ranked candidate ML models such that the confirmed ML models may answer the request.
    Type: Application
    Filed: December 24, 2018
    Publication date: June 25, 2020
    Inventors: Dhruv Chaudhari, Harshil Shah, Amitabh Jain, Monish Mangalkumar Darda