Methods to reduce the diversity of double-sided machine learning models

By coordinating machine learning model selection and usage between user equipment and network nodes through profile exchange, the method addresses resource inefficiencies and hardware shortages in two-sided machine learning systems.

JP7868257B2Active Publication Date: 2026-06-01NOKIA TECHNOLOGIES OY
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Patent Information

Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
NOKIA TECHNOLOGIES OY
Filing Date
2023-09-21
Publication Date
2026-06-01

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Abstract

An apparatus is provided, comprising means for performing the following: transmitting information regarding at least one two-sided machine learning model supported by the device to a network node; or transmitting a machine learning profile identity of the device to a network node, wherein the machine learning profile identity is associated with at least one two-sided machine learning model supported by the device, and the at least one two-sided machine learning model is configured to enable joint inference by the device and the network node; and receiving from the network node an indication of at least a first selected two-sided machine learning model supported by the device.
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