Patents by Inventor Janice Lan

Janice Lan 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 configuring a subscriber-specific ensemble of machine learning models
    Patent number: 10666674
    Abstract: A machine learning-based system and method for identifying digital threats that includes implementing a machine learning-based digital threat mitigation service over a distributed network of computers; constructing, by the machine learning-based digital threat mitigation service, a subscriber-specific machine learning ensemble that includes a plurality of distinct machine learning models, wherein each of the plurality of distinct machine learning models is configured to perform a distinct machine learning task for identifying a digital threat or digital fraud; constructing a corpus of subscriber-specific digital activity data for training the plurality of distinct machine learning models of the subscriber-specific ensemble; training the subscriber-specific ensemble using at least the corpus of subscriber-specific digital activity data; and deploying the subscriber-specific ensemble.
    Type: Grant
    Filed: October 16, 2019
    Date of Patent: May 26, 2020
    Assignee: Sift Science, Inc.
    Inventors: Fred Sadaghiani, Alex Paino, Jacob Burnim, Janice Lan
  • Systems and methods configuring a subscriber-specific ensemble of machine learning models
    Patent number: 10491617
    Abstract: A machine learning-based system and method for identifying digital threats that includes implementing a machine learning-based digital threat mitigation service over a distributed network of computers; constructing, by the machine learning-based digital threat mitigation service, a subscriber-specific machine learning ensemble that includes a plurality of distinct machine learning models, wherein each of the plurality of distinct machine learning models is configured to perform a distinct machine learning task for identifying a digital threat or digital fraud; constructing a corpus of subscriber-specific digital activity data for training the plurality of distinct machine learning models of the subscriber-specific ensemble; training the subscriber-specific ensemble using at least the corpus of subscriber-specific digital activity data; and deploying the subscriber-specific ensemble.
    Type: Grant
    Filed: May 31, 2019
    Date of Patent: November 26, 2019
    Assignee: Sift Science, Inc.
    Inventors: Fred Sadaghiani, Alex Paino, Jacob Burnim, Janice Lan