Patents by Inventor Martine Ivonne Leo De Cock

Martine Ivonne Leo De Cock 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).

  • CRYPTOGRAPHICALLY SECURE MACHINE LEARNING
    Publication number: 20200005180
    Abstract: Embodiments are directed towards classifying data. A machine learning (ML) engine may select an ML model that may employ a cryptographic multi-party computation (MPC) protocol based on model preferences, including a parameter model, provided by a client. A randomness engine may be employed to provide random values and other random values based on the MPC protocol such that the random values may be provided to the client and the other random values may be provided to an answer engine. Input values that correspond to fields in the parameter model may be provided by the client such that the input values may be based on the MPC protocol and the random values. The answer engine may be employed to provide partial results to the question based on the ML model, the input values, and the MPC protocol that may be provided to the client.
    Type: Application
    Filed: February 4, 2019
    Publication date: January 2, 2020
    Inventors: Kyle Josiah Fritchman, Tyler John Hughes, Ankur Teredesai, Martine Ivonne Leo De Cock, Anderson Nascimento
  • Cryptographically secure machine learning
    Patent number: 10198399
    Abstract: Embodiments are directed towards classifying data. A machine learning (ML) engine may select an ML model that may employ a cryptographic multi-party computation (MPC) protocol based on model preferences, including a parameter model, provided by a client. A randomness engine may be employed to provide random values and other random values based on the MPC protocol such that the random values may be provided to the client and the other random values may be provided to an answer engine. Input values that correspond to fields in the parameter model may be provided by the client such that the input values may be based on the MPC protocol and the random values. The answer engine may be employed to provide partial results to the question based on the ML model, the input values, and the MPC protocol that may be provided to the client.
    Type: Grant
    Filed: March 6, 2018
    Date of Patent: February 5, 2019
    Assignee: KenSci Inc.
    Inventors: Kyle Josiah Fritchman, Tyler John Hughes, Ankur Teredesai, Martine Ivonne Leo De Cock, Anderson Nascimento