Patents by Inventor David Duling

David Duling 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).

  • Systems and methods for providing a unified variable selection approach based on variance preservation
    Patent number: 9501522
    Abstract: This disclosure describes a method, system and computer-program product for parallelized feature selection. The method, system and computer-program product may be used to access a first set of features, wherein the first set of features includes multiple features, wherein the features are characterized by a variance measure, and wherein accessing the first set of features includes using a computing system to access the features, determine components of a covariance matrix, the components of the covariance matrix indicating a covariance with respect to pairs of features in the first set, and select multiple features from the first set, wherein selecting is based on the determined components of the covariance matrix and an amount of the variance measure attributable to the selected multiple features, and wherein selecting the multiple features includes executing a greedy search performed using parallelized computation.
    Type: Grant
    Filed: August 19, 2013
    Date of Patent: November 22, 2016
    Assignee: SAS Institute Inc.
    Inventors: Zheng Zhao, James Cox, David Duling, Warren Sarle
  • Systems and Methods for Providing a Unified Variable Selection Approach Based on Variance Preservation
    Publication number: 20140059073
    Abstract: This disclosure describes a method, system and computer-program product for parallelized feature selection. The method, system and computer-program product may be used to access a first set of features, wherein the first set of features includes multiple features, wherein the features are characterized by a variance measure, and wherein accessing the first set of features includes using a computing system to access the features, determine components of a covariance matrix, the components of the covariance matrix indicating a covariance with respect to pairs of features in the first set, and select multiple features from the first set, wherein selecting is based on the determined components of the covariance matrix and an amount of the variance measure attributable to the selected multiple features, and wherein selecting the multiple features includes executing a greedy search performed using parallelized computation.
    Type: Application
    Filed: August 19, 2013
    Publication date: February 27, 2014
    Applicant: SAS Institute Inc.
    Inventors: Zheng Zhao, James Cox, David Duling, Warren Sarle