Patents by Inventor Uri Stemmer

Uri Stemmer 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).

  • Patent number: 11023594
    Abstract: Technologies are disclosed for computing heavy hitter histograms using locally private randomization. Under this strategy, “agents” can each hold a “type” derived from a large dictionary. By performing an algorithm, an estimate of the distribution of data can be obtained. Two algorithms implement embodiments for performing methods involving differential privacy for one or more users, and usually are run in the local model. This means that information is collected from the agents with added noise to hide the agents' individual contributions to the histogram. The result is an accurate enough estimate of the histogram for commercial or other applications relating to the data collection of one or more agents. Specifically, the proposed algorithms improve on the performance (measured in computation and memory requirements at the server and the agent, as well as communication volume) of previously solutions.
    Type: Grant
    Filed: May 22, 2018
    Date of Patent: June 1, 2021
    Assignee: Georgetown University
    Inventors: Yaacov Nissim Kobliner, Uri Stemmer, Raef Bahi Youssef Bassily, Abhradeep Guha Thakurta
  • Publication number: 20180336357
    Abstract: Technologies are disclosed for computing heavy hitter histograms using locally private randomization. Under this strategy, “agents” can each hold a “type” derived from a large dictionary. By performing an algorithm, an estimate of the distribution of data can be obtained. Two algorithms implement embodiments for performing methods involving differential privacy for one or more users, and usually are run in the local model. This means that information is collected from the agents with added noise to hide the agents' individual contributions to the histogram. The result is an accurate enough estimate of the histogram for commercial or other applications relating to the data collection of one or more agents. Specifically, the proposed algorithms improve on the performance (measured in computation and memory requirements at the server and the agent, as well as communication volume) of previously solutions.
    Type: Application
    Filed: May 22, 2018
    Publication date: November 22, 2018
    Applicants: Georgetown University, President and Fellows of Harvard College, The Regents of the University of California
    Inventors: Yaacov Nissim Kobliner, Uri Stemmer, Raef Bahi Youssef Bassily, Abhradeep Guha Thakurta