Patents by Inventor Mustafa Kabul

Mustafa Kabul 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).

  • Methods and systems for reinforcement learning
    Patent number: 10762424
    Abstract: Exemplary embodiments can maximize long-term value in a machine learning system. The system may employ an offline training process and an online training process. In the offline training process, an initial policy is learned to provide a warm start to the online training process. In the online training process, the system applies concurrent reinforcement learning across multiple environments, with the goal of learning efficient policies in real time from in-flight user data in one environment, and applying the learned policies to other environments. With the combination of offline training and online training, the system is able to improve initial performance through the warm start, while adapting to a changing context through concurrent reinforcement learning.
    Type: Grant
    Filed: September 11, 2018
    Date of Patent: September 1, 2020
    Assignee: SAS INSTITUTE INC.
    Inventors: Mohammad Reza Nazari, Afshin Oroojlooy Jadid, Mustafa Kabul
  • METHODS AND SYSTEMS FOR REINFORCEMENT LEARNING
    Publication number: 20190102676
    Abstract: Exemplary embodiments can maximize long-term value in a machine learning system. The system may employ an offline training process and an online training process. In the offline training process, an initial policy is learned to provide a warm start to the online training process. In the online training process, the system applies concurrent reinforcement learning across multiple environments, with the goal of learning efficient policies in real time from in-flight user data in one environment, and applying the learned policies to other environments. With the combination of offline training and online training, the system is able to improve initial performance through the warm start, while adapting to a changing context through concurrent reinforcement learning.
    Type: Application
    Filed: September 11, 2018
    Publication date: April 4, 2019
    Applicant: SAS Institute Inc.
    Inventors: Mohammad Reza Nazari, Afshin Orooiloov Jadid, Mustafa Kabul