WO2026022610 - ENSURE CONSISTENCY FOR MACHINE LEARNING PROCEDURE
National phase entry is expected:
Publication Number
WO/2026/022610
Publication Date
29.01.2026
International Application No.
PCT/IB2025/057115
International Filing Date
14.07.2025
Title **
[English]
ENSURE CONSISTENCY FOR MACHINE LEARNING PROCEDURE
[French]
GARANTIE DE COHÉRENCE POUR UNE PROCÉDURE D'APPRENTISSAGE AUTOMATIQUE
Applicants **
NOKIA TECHNOLOGIES OY
Inventors
CARRILLO MELGAREJO, Dick
Priority Data
2410878.9
25.07.2024
GB
Application details
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International Searching Authority |
EPO
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| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
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| Type of Assignment |
The Standard Agent's Assignment
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| Applicant's Legal Status |
Legal Entity
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| Entry into National Phase under |
Chapter I
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| Patent Delivery |
Send the Letters Patent by Courier
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| 译文 |
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Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 2297 | |
| EPO | Filing, Examination, Granting | 11522 | |
| Japan | Filing, Examination, Granting | 2340 | |
| South Korea | Filing, Examination, Granting | 2449 | |
| USA | Filing, Examination, Granting | 7340 |
Total:
25,948
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Abstract[English]
Example embodiments of the present disclosure are directed to a solution for ensuring consistency for artificial intelligence (AI)/machine learning (ML) procedure A method comprises receiving, from a second apparatus, configuration information associated with a second machine learning (ML) phase, wherein the configuration information comprising at least one association indicator; and determining, based on the at least one association indicator, a first configuration from a set of first configurations, each of the set of first configurations being associated with a respective association indicator and comprising at least one associated identity used by the first apparatus during a first ML phase, each associated identity corresponding to an additional condition of network.[French]
Des modes de réalisation donnés à titre d'exemple de la présente divulgation concernent une solution permettant de garantir la cohérence pour une procédure d'intelligence artificielle (IA)/d'apprentissage automatique (ML). Un procédé consiste à recevoir, en provenance d'un second appareil, des informations de configuration associées à une seconde phase d'apprentissage automatique (ML), les informations de configuration comprenant au moins un indicateur d'association ; et à déterminer, sur la base de l'au moins un indicateur d'association, une première configuration parmi un ensemble de premières configurations, chacune de l'ensemble de premières configurations étant associée à un indicateur d'association respectif et comprenant au moins une identité associée utilisée par le premier appareil pendant une première phase de ML, chaque identité associée correspondant à une condition supplémentaire de réseau.