Patents by Inventor Robbie A. Haertel

Robbie A. Haertel 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 model evaluation and training based on utility
    Patent number: 10515313
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a plurality of different types of predictive models using training data, wherein each of the predictive models implements a different machine learning technique. One or more weights are obtained wherein each weight is associated with an answer category in the plurality of examples. A weighted accuracy is calculated for each of the predictive models using the one or more weights.
    Type: Grant
    Filed: October 29, 2014
    Date of Patent: December 24, 2019
    Assignee: Google LLC
    Inventors: Robert Kaplow, Wei-Hao Lin, Gideon S. Mann, Travis H. K. Green, Gang Fu, Robbie A. Haertel
  • Predictive Model Evaluation and Training Based on Utility
    Publication number: 20150186800
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a plurality of different types of predictive models using training data, wherein each of the predictive models implements a different machine learning technique. One or more weights are obtained wherein each weight is associated with an answer category in the plurality of examples. A weighted accuracy is calculated for each of the predictive models using the one or more weights.
    Type: Application
    Filed: October 29, 2014
    Publication date: July 2, 2015
    Inventors: Robert Kaplow, Wei-Hao Lin, Gideon S. Mann, Travis H.K. Green, Gang Fu, Robbie A. Haertel
  • Predictive model evaluation and training based on utility
    Patent number: 8909564
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a plurality of different types of predictive models using training data, wherein each of the predictive models implements a different machine learning technique. One or more weights are obtained wherein each weight is associated with an answer category in the plurality of examples. A weighted accuracy is calculated for each of the predictive models using the one or more weights.
    Type: Grant
    Filed: September 1, 2011
    Date of Patent: December 9, 2014
    Assignee: Google Inc.
    Inventors: Robert Kaplow, Wei-Hao Lin, Gideon S. Mann, Travis H. K. Green, Gang Fu, Robbie A. Haertel