Patents by Inventor Stefania Costache

Stefania Costache 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).

  • Event-based task processing system and method based on a stateful distributed streaming queue
    Patent number: 11853815
    Abstract: Various methods, apparatuses/systems, and media for event-based task processing are disclosed. The system includes a processor and a memory operatively connected to the processor via a communication interface.
    Type: Grant
    Filed: July 28, 2022
    Date of Patent: December 26, 2023
    Assignee: JPMORGAN CHASE BANK, N.A.
    Inventors: Stefania Costache, Ioana Nistoreanu, Niraj Khandekar
  • Runtime estimation for machine learning tasks
    Patent number: 11727309
    Abstract: Techniques for estimating runtimes of one or more machine learning tasks are provided. For example, one or more embodiments described herein can regard a system that can comprise a memory that stores computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise an extraction component that can extract a parameter from a machine learning task. The parameter can define a performance characteristic of the machine learning task. Also, the computer executable components can comprise a model component that can generate a model based on the parameter. Further, the computer executable components can comprise an estimation component that can generate an estimated runtime of the machine learning task based on the model.
    Type: Grant
    Filed: October 28, 2021
    Date of Patent: August 15, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Parijat Dube, Gauri Joshi, Priya Ashok Nagpurkar, Stefania Costache, Diana Jeanne Arroyo, Zehra Noman Sura
  • RUNTIME ESTIMATION FOR MACHINE LEARNING TASKS
    Publication number: 20220051142
    Abstract: Techniques for estimating runtimes of one or more machine learning tasks are provided. For example, one or more embodiments described herein can regard a system that can comprise a memory that stores computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise an extraction component that can extract a parameter from a machine learning task. The parameter can define a performance characteristic of the machine learning task. Also, the computer executable components can comprise a model component that can generate a model based on the parameter. Further, the computer executable components can comprise an estimation component that can generate an estimated runtime of the machine learning task based on the model.
    Type: Application
    Filed: October 28, 2021
    Publication date: February 17, 2022
    Inventors: Parijat Dube, Gauri Joshi, Priya Ashok Nagpurkar, Stefania Costache, Diana Jeanne Arroyo, Zehra Noman Sura
  • Runtime estimation for machine learning tasks
    Patent number: 11200512
    Abstract: Techniques for estimating runtimes of one or more machine learning tasks are provided. For example, one or more embodiments described herein can regard a system that can comprise a memory that stores computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise an extraction component that can extract a parameter from a machine learning task. The parameter can define a performance characteristic of the machine learning task. Also, the computer executable components can comprise a model component that can generate a model based on the parameter. Further, the computer executable components can comprise an estimation component that can generate an estimated runtime of the machine learning task based on the model.
    Type: Grant
    Filed: February 21, 2018
    Date of Patent: December 14, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Parijat Dube, Gauri Joshi, Priya Ashok Nagpurkar, Stefania Costache, Diana Jeanne Arroyo, Zehra Noman Sura