The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 27, 2026

Filed:

Sep. 10, 2021
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Ganesh Ananthanarayanan, Seattle, WA (US);

Anand Padmanabha Iyer, Redmond, WA (US);

Yuanchao Shu, Kirkland, WA (US);

Nikolaos Karianakis, Sammamish, WA (US);

Arthi Hema Padmanabhan, Redmond, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06V 20/40 (2022.01);
U.S. Cl.
CPC ...
G06N 20/00 (2019.01); G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06V 20/40 (2022.01);
Abstract

Systems and methods are provided for merging models for use in an edge server under the multi-access edge computing environment. In particular, a model merger selects a layer of a model based on a level of memory consumption in the edge server and determines sharable layers based on common properties of the selected layer. The model merger generates a merged model by generating a single instantiation of a layer that corresponds to the sharable layers. A model trainer trains the merged model based on training data for the respective models to attain a level of accuracy of data analytics above a predetermined threshold. The disclosed technology further refreshes the merged model upon observing a level of data drift that exceeds a predetermined threshold. The refreshing of the merged model includes detaching and/or splitting consolidated sharable layers of sub-models in the merged model. By merging models, the disclosed technology reduces memory footprints of models used in the edge server, rectifying memory scarcity issues in the edge server.


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