Invention Grant
- Patent Title: Dynamically modifying a boundary of a deep learning network
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Application No.: US14506972Application Date: 2014-10-06
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Publication No.: US10679140B2Publication Date: 2020-06-09
- Inventor: Kevin Arthur Gomez , Frank Dropps , Ryan James Goss , Jon Trantham , Antoine Khoueir
- Applicant: Seagate Technology LLC
- Applicant Address: US CA Cupertino
- Assignee: Seagate Technology LLC
- Current Assignee: Seagate Technology LLC
- Current Assignee Address: US CA Cupertino
- Agency: Mueting Raasch Group
- Main IPC: G06N20/00
- IPC: G06N20/00 ; H04L29/08 ; G06N7/00 ; G06N3/04

Abstract:
A connection between a user device and a network server is established. Via the connection, a deep learning network is formed for a processing task. A first portion of the deep learning network operates on the user device and a second portion of the deep learning network operates on the network server. Based on cooperation between the user device and the network server, a boundary between the first portion and the second portion of the deep learning network is dynamically modified based on a change in a performance indicator that could affect the processing task.
Public/Granted literature
- US20160098646A1 DYNAMICALLY MODIFYING A BOUNDARY OF A DEEP LEARNING NETWORK Public/Granted day:2016-04-07
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