Invention Grant
- Patent Title: Automatic object optimization to accelerate machine learning training
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Application No.: US16369694Application Date: 2019-03-29
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Publication No.: US11715030B2Publication Date: 2023-08-01
- Inventor: Huamin Chen , Dennis R. C. Keefe
- Applicant: Red Hat, Inc.
- Applicant Address: US NC Raleigh
- Assignee: Red Hat, Inc.
- Current Assignee: Red Hat, Inc.
- Current Assignee Address: US NC Raleigh
- Agency: Dority & Manning, P.A.
- Main IPC: G06F12/00
- IPC: G06F12/00 ; G06N20/00 ; G06F16/215 ; G06F3/06 ; G06F18/214

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.
Public/Granted literature
- US20200311599A1 AUTOMATIC OBJECT OPTIMIZATION TO ACCELERATE MACHINE LEARNING TRAINING Public/Granted day:2020-10-01
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