Patents by Inventor Timothy Galvin

Timothy Galvin 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 low-rank matrix approximation
    Patent number: 10318608
    Abstract: Systems and methods may identify at least a first set of right singular vectors and a first set of singular values of a subset of the matrix, reduce the subset by an amount of energy of a selected data entry of the subset based on the first set of right singular vectors and the first set of singular values, incorporate a new data entry from the matrix into the subset, update the first set of right singular vectors and the first set of singular values of the subset based on the new data entry by a singular value decomposition (SVD) update, and generate the low-rank approximation of the matrix based on the updated first set of right singular vectors and the updated first set of singular values.
    Type: Grant
    Filed: August 21, 2015
    Date of Patent: June 11, 2019
    Assignees: MASSACHUSETTS INSTITUTE OF TECHNOLOGY, THE CHARLES STARK DRAPER LABORATORY, INC.
    Inventors: Timothy Galvin, Christopher C. Yu, Piotr Indyk, Lei Hamilton, William Whitacre
  • SYSTEMS AND METHODS FOR LOW-RANK MATRIX APPROXIMATION
    Publication number: 20160055124
    Abstract: Systems and methods for generating a low-rank approximation of a matrix are provided. The various systems and methods may identify at least a first set of right singular vectors and a first set of singular values of a subset of the matrix, reduce the subset by an amount of energy of a selected data entry of the subset based on the first set of right singular vectors and the first set of singular values, incorporate a new data entry from the matrix into the subset, update the first set of right singular vectors and the first set of singular values of the subset based on the new data entry by a singular value decomposition (SVD) update, and generate the low-rank approximation of the matrix based on the updated first set of right singular vectors and the updated first set of singular values.
    Type: Application
    Filed: August 21, 2015
    Publication date: February 25, 2016
    Inventors: Timothy Galvin, Christopher C. Yu, Piotr Indyk, Lei Hamilton, William Whitacre