Patents by Inventor Dennis R. C. Keefe

Dennis R. C. Keefe 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: 11715030
    Abstract: Automatic object optimization to accelerate machine learning training is disclosed. A request for a machine learning training dataset comprising a plurality of objects is received from a requestor. The plurality of objects includes data for training a machine learning model. A uniqueness characteristic for objects of the plurality of objects is determined, the uniqueness characteristic being indicative of how unique each object is relative to each other object. A group of objects from the plurality of objects is sent to the requestor, the group of objects being selected based at least partially on the uniqueness characteristic or sent in an order based at least partially on the uniqueness characteristic.
    Type: Grant
    Filed: March 29, 2019
    Date of Patent: August 1, 2023
    Assignee: Red Hat, Inc.
    Inventors: Huamin Chen, Dennis R. C. Keefe
  • Patent number: 11392610
    Abstract: Scalable object storage with intelligent replication is disclosed. A container image storage system executing on one or more processor devices receives a container image comprising a plurality of objects. For each object, a reference count indicative of how many different container images stored in the container image storage system include the object is determined. For each object, a number of copies of the object to be stored in a storage based on the reference count is determined. For each object, the number of copies of the object are stored in the storage.
    Type: Grant
    Filed: October 5, 2018
    Date of Patent: July 19, 2022
    Assignee: Red Hat, Inc.
    Inventors: Huamin Chen, Dennis R. C. Keefe
  • Publication number: 20200311599
    Abstract: Automatic object optimization to accelerate machine learning training is disclosed. A request for a machine learning training dataset comprising a plurality of objects is received from a requestor. The plurality of objects includes data for training a machine learning model. A uniqueness characteristic for objects of the plurality of objects is determined, the uniqueness characteristic being indicative of how unique each object is relative to each other object. A group of objects from the plurality of objects is sent to the requestor, the group of objects being selected based at least partially on the uniqueness characteristic or sent in an order based at least partially on the uniqueness characteristic.
    Type: Application
    Filed: March 29, 2019
    Publication date: October 1, 2020
    Inventors: Huamin Chen, Dennis R. C. Keefe
  • Publication number: 20200110830
    Abstract: Scalable object storage with intelligent replication is disclosed. A container image storage system executing on one or more processor devices receives a container image comprising a plurality of objects. For each object, a reference count indicative of how many different container images stored in the container image storage system include the object is determined. For each object, a number of copies of the object to be stored in a storage based on the reference count is determined. For each object, the number of copies of the object are stored in the storage.
    Type: Application
    Filed: October 5, 2018
    Publication date: April 9, 2020
    Inventors: Huamin Chen, Dennis R. C. Keefe