Patents by Inventor Andrew K. Story

Andrew K. Story 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).

  • Reduction of computation complexity of neural network sensitivity analysis
    Patent number: 11100392
    Abstract: As part of neural network sensitivity analyses, base outputs of hidden layer nodes of a neural network model for non-perturbed variables can be reused when perturbing the variables. Such an arrangement greatly reduces complexity of the calculations required to generate outputs of the model. Related apparatus, systems, techniques and articles are also described.
    Type: Grant
    Filed: October 31, 2016
    Date of Patent: August 24, 2021
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Xing Zhao, Peter Hamilton, Andrew K. Story
  • Generation of a boosted ensemble of segmented scorecard models
    Patent number: 10366342
    Abstract: Data is received that include values that correspond to a plurality of variables. A score is then generated based on the received data and using a boosted ensemble of segmented scorecard models. The boosted ensemble of segmented scorecard models includes two or more segmented scorecard models. Subsequently, data including the score can be provided (e.g., displayed, transmitted, loaded, stored, etc.). Related apparatus, systems, techniques and articles are also described.
    Type: Grant
    Filed: March 10, 2014
    Date of Patent: July 30, 2019
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Xing Zhao, Peter Hamilton, Andrew K. Story
  • Reduction of Computation Complexity of Neural Network Sensitivity Analysis
    Publication number: 20170177996
    Abstract: As part of neural network sensitivity analyses, base outputs of hidden layer nodes of a neural network model for non-perturbed variables can be reused when perturbing the variables. Such an arrangement greatly reduces complexity of the calculations required to generate outputs of the model. Related apparatus, systems, techniques and articles are also described.
    Type: Application
    Filed: October 31, 2016
    Publication date: June 22, 2017
    Inventors: Xing Zhao, Peter Hamilton, Andrew K. Story
  • Reduction of computation complexity of neural network sensitivity analysis
    Patent number: 9483727
    Abstract: As part of neural network sensitivity analysis, base outputs of hidden layer nodes of a neural network model for non-perturbed variables can be reused when perturbing the variables. Such an arrangement greatly reduces complexity of the calculations required to generate outputs of the model. Related apparatus, systems, techniques and articles are also described.
    Type: Grant
    Filed: September 18, 2013
    Date of Patent: November 1, 2016
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Xing Zhao, Peter Hamilton, Andrew K. Story
  • Scorecard models with measured variable interactions
    Patent number: 9367520
    Abstract: Data is received that characterizes a transaction and includes a plurality of values corresponding to variables. Thereafter, a score is determined for the transaction based on the received data and using a scoring model. The scoring model only uses variables pairs having a divergence residual above a pre-defined threshold. Thereafter, data is provided that characterizes the determined score. Related apparatus, systems, techniques and computer program products are also described.
    Type: Grant
    Filed: December 20, 2012
    Date of Patent: June 14, 2016
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Xing Zhao, Peter Hamilton, Andrew K. Story, Andrew Flint
  • Boosted Ensemble of Segmented Scorecard Models
    Publication number: 20150254568
    Abstract: Data is received that include values that correspond to a plurality of variables. A score is then generated based on the received data and using a boosted ensemble of segmented scorecard models. The boosted ensemble of segmented scorecard models includes two or more segmented scorecard models. Subsequently, data including the score can be provided (e.g., displayed, transmitted, loaded, stored, etc.). Related apparatus, systems, techniques and articles are also described.
    Type: Application
    Filed: March 10, 2014
    Publication date: September 10, 2015
    Applicant: FAIR ISAAC CORPORATION
    Inventors: Xing Zhao, Peter Hamilton, Andrew K. Story
  • Reduction of Computation Complexity of Neural Network Sensitivity Analysis
    Publication number: 20150081606
    Abstract: As part of neural network sensitivity analysis, base outputs of hidden layer nodes of a neural network model for non-perturbed variables can be reused when perturbing the variables. Such an arrangement greatly reduces complexity of the calculations required to generate outputs of the model. Related apparatus, systems, techniques and articles are also described.
    Type: Application
    Filed: September 18, 2013
    Publication date: March 19, 2015
    Applicant: FAIR ISAAC CORPORATION
    Inventors: Xing Zhao, Peter Hamilton, Andrew K. Story
  • Scorecard Models with Measured Variable Interactions
    Publication number: 20140180649
    Abstract: Data is received that characterizes a transaction and includes a plurality of values corresponding to variables. Thereafter, a score is determined for the transaction based on the received data and using a scoring model. The scoring model only uses variables pairs having a divergence residual above a pre-defined threshold. Thereafter, data is provided that characterizes the determined score. Related apparatus, systems, techniques and computer program products are also described.
    Type: Application
    Filed: December 20, 2012
    Publication date: June 26, 2014
    Applicant: FAIR ISAAC CORPORATION
    Inventors: Xing Zhao, Peter Hamilton, Andrew K. Story, Andrew Flint