Methods, apparatus and machine-readable media relating to machine-learning in a communication network
AssigneeTelefonaktiebolaget LM Ericsson (publ)
InventorsKarl Norrman, Martin Isaksson
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Abstract
A method performed by a first network entity in a communications network includes training a model to obtain a local model update including an update to values of one or more parameters of the model, in which training the model includes inputting training data into a machine learning algorithm. The method further includes applying a serialisation function to the local model update to construct a serial representation of the local model update, thereby removing information indicative of a structure of the model, and transmitting the serial representation of the local model update to an aggregator entity in the communications network.
Claims20
A method performed by a first network entity in a communications network, the method comprising:
- training a model to obtain a local model update comprising an update to values of one or more parameters of the model, wherein training the model comprises inputting training data into a machine learning algorithm;
- generating a serial representation of the local model update without information indicative of a structure of the model by applying a serialization function to the local model update;
- and
- transmitting the serial representation of the local model update to an aggregator entity in the communications network.
A first network entity for a communications network, the first network entity comprising:
- processing circuitry;
- and
- a memory coupled to the processing circuitry and having instructions stored therein that are executable by the processing circuitry to cause the first network entity to perform operations comprising:
- training a model to obtain a local model update comprising an update to values of one or more parameters of the model, wherein training the model comprises inputting training data into a machine learning algorithm;
- generating a serial representation of the local model update without information indicative of a structure of the model by applying a serialization function to the local model update;
- and
- transmitting the serial representation of the local model update to an aggregator entity in the communications network.
A system in a communications network, the system comprising:
- an aggregator entity;
- and
- a plurality of network entities configured to perform operations comprising:
- training a model to obtain a local model update comprising an update to values of one or more parameters of the model, wherein training the model comprises inputting training data into a machine learning algorithm;
- generating a serial representation of the local model update without information indicative of a structure of the model by applying a serialization function to the local model update;
- and
- transmitting the serial representation of the local model update to the aggregator entity, wherein the aggregator entity is configured to combine the local model updates received from the plurality of network entities to obtain a combined model update.
Dependencies are inferred from the claim text.