PREDICTING THE IMPACT OF NETWORK SOFTWARE UPGRADES ON MACHINE LEARNING MODEL PERFORMANCE

Patent №

US 11,625,241

Granted

2023-04-11

Filed 2022

Owner

CISCO TECHNOLOGY, INC.

Lab

AI components

3

ml · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

17874509

In one embodiment, a service receives software version data regarding versions of software executed by devices in a network. The service detects a version change in the version of software executed by one or more of the devices, based on the received software version data. The service makes a determination that a drop in data quality of input data for a machine learning model used to monitor the network is associated with the detected version change. The service reverts the one or more devices to a prior version of software, based on the determination that the drop in quality of the input data for the machine learning model used to monitor the network is associated with the detected version change.

Machine learningPlanningAI hardwareG06F 8/71G06F 8/62G06N 20/00H04L 41/082H04L 41/0863H04L 41/142H04L 41/147H04L 41/16+3 more

AI classification

Planning1.00
AI hardware1.00
Machine learning0.97
Knowledge representation0.22
Natural language0.00
Evolutionary computation0.00
Speech0.00
Vision0.00

Ownership

CISCO TECHNOLOGY, INC.

assignment · 606390470

Assignors

KOLAR, VINAY KUMAR, VASSEUR, JEAN-PHILIPPE, MERMOUD, GRÉGORY, SAVALLE, PIERRE-ANDRÉ

On an employer assignment, the assignors are typically the inventors.

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