Patents by Inventor Moritz A.W. Hardt

Moritz A.W. Hardt 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).

  • Machine learning with incomplete data sets
    Patent number: 9349105
    Abstract: Machine learning solutions compensate for data missing from input (training) data and thereby arrive at a predictive model that is based upon, and consistent with, the training data. The predictive model can be generated within a learning algorithm framework by transforming the training data to generate modality or similarity kernels. Similarity values can be generated for these missing similarity values.
    Type: Grant
    Filed: December 18, 2013
    Date of Patent: May 24, 2016
    Assignee: International Business Machines Corporation
    Inventors: David J. Beymer, Karen W. Brannon, Ting Chen, Moritz A. W. Hardt, Ritwik K. Kumar, Tanveer F. Syeda-Mahmood
  • MACHINE LEARNING WITH INCOMPLETE DATA SETS
    Publication number: 20150170055
    Abstract: Machine learning solutions compensate for data missing from input (training) data and thereby arrive at a predictive model that is based upon, and consistent with, the training data. The predictive model can be generated within a learning algorithm framework by transforming the training data to generate modality or similarity kernels. Similarity values can be generated for these missing similarity values.
    Type: Application
    Filed: December 18, 2013
    Publication date: June 18, 2015
    Applicant: International Business Machines Corporation
    Inventors: David J. Beymer, Karen W. Brannon, Ting Chen, Moritz A. W. Hardt, Ritwik K. Kumar, Tanveer F. Syeda-Mahmood
  • Geometric mechanism for privacy-preserving answers
    Patent number: 8661047
    Abstract: A system for answering sets of queries on a set of private data while providing differential privacy protection is provided. The set of queries is received and applied to the set of private data to generate a set of results or answers. A geometric representation of the set of queries is generated. Example geometric representations include polytopes. Error values are generated for the set of queries using a K-norm mechanism based on values sampled from the geometric representation. The sampled values are added to the set of results to provide the differential privacy protection. By generating the error values based on the set of queries rather than the set of results or the set of private data, the amount of error added to the generated results to achieve a level of differential privacy protection is reduced.
    Type: Grant
    Filed: May 17, 2010
    Date of Patent: February 25, 2014
    Assignee: Microsoft Corporation
    Inventors: Kunal Talwar, Moritz A. W. Hardt
  • GEOMETRIC MECHANISM FOR PRIVACY-PRESERVING ANSWERS
    Publication number: 20110282865
    Abstract: A system for answering sets of queries on a set of private data while providing differential privacy protection is provided. The set of queries is received and applied to the set of private data to generate a set of results or answers. A geometric representation of the set of queries is generated. Example geometric representations include polytopes. Error values are generated for the set of queries using a K-norm mechanism based on values sampled from the geometric representation. The sampled values are added to the set of results to provide the differential privacy protection. By generating the error values based on the set of queries rather than the set of results or the set of private data, the amount of error added to the generated results to achieve a level of differential privacy protection is reduced.
    Type: Application
    Filed: May 17, 2010
    Publication date: November 17, 2011
    Applicant: Microsoft Corporation
    Inventors: Kunal Talwar, Moritz A.W. Hardt