Patents by Inventor Arno Candel

Arno Candel 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).

  • EVOLVED MACHINE LEARNING MODELS
    Publication number: 20230074025
    Abstract: A plurality of initial machine learning models are determined based on a plurality of original features. The plurality of initial machine learning models are filtered by selecting a subset of the initial machine learning models as one or more surviving machine learning models. One or more evolved machine learning models are generated. At least one of the evolved machine learning models is based at least in part on one or more new features, which are based at least in part on a transformation of at least one of features of the one or more surviving machine learning models. Corresponding validation scores associated with the one or more evolved machine learning models and corresponding validation scores associated with the one or more surviving machine learning models are compared. At least one of the one or more evolved machine learning models or the one or more surviving machine learning models are selected as one or more new selected surviving machine learning models.
    Type: Application
    Filed: August 23, 2022
    Publication date: March 9, 2023
    Inventors: Arno Candel, Dmitry Larko, SriSatish Ambati, Prithvi Prabhu, Mark Landry, Jonathan C. McKinney
  • Evolved machine learning models
    Patent number: 11475372
    Abstract: A plurality of initial machine learning models are determined based on a plurality of original features. The plurality of initial machine learning models are filtered by selecting a subset of the initial machine learning models as one or more surviving machine learning models. One or more evolved machine learning models are generated. At least one of the evolved machine learning models is based at least in part on one or more new features, which are based at least in part on a transformation of at least one of features of the one or more surviving machine learning models. Corresponding validation scores associated with the one or more evolved machine learning models and corresponding validation scores associated with the one or more surviving machine learning models are compared. At least one of the one or more evolved machine learning models or the one or more surviving machine learning models are selected as one or more new selected surviving machine learning models.
    Type: Grant
    Filed: February 27, 2019
    Date of Patent: October 18, 2022
    Assignee: H2O.ai Inc.
    Inventors: Arno Candel, Dmitry Larko, SriSatish Ambati, Prithvi Prabhu, Mark Landry, Jonathan C. McKinney
  • EVOLVED MACHINE LEARNING MODELS
    Publication number: 20190295000
    Abstract: A plurality of initial machine learning models are determined based on a plurality of original features. The plurality of initial machine learning models are filtered by selecting a subset of the initial machine learning models as one or more surviving machine learning models. One or more evolved machine learning models are generated. At least one of the evolved machine learning models is based at least in part on one or more new features, which are based at least in part on a transformation of at least one of features of the one or more surviving machine learning models. Corresponding validation scores associated with the one or more evolved machine learning models and corresponding validation scores associated with the one or more surviving machine learning models are compared. At least one of the one or more evolved machine learning models or the one or more surviving machine learning models are selected as one or more new selected surviving machine learning models.
    Type: Application
    Filed: February 27, 2019
    Publication date: September 26, 2019
    Inventors: Arno Candel, Dmitry Larko, SriSatish Ambati, Prithvi Prabhu, Mark Landry, Jonathan C. McKinney