Obtaining parameters for a learning model with normalization layers

Abstract

Various aspects of the present disclosure relate to obtaining parameters for a learning model with normalization layers. An apparatus, such as a network equipment (NE), generates a first set of parameters that are common for a set of learning models (e.g., machine learning models and / or artificial intelligence (AI) models) and respective second sets of parameters for each learning model in the set of learning models. The respective second sets of parameters are parameters of one or more normalization layers of learning models in the set of learning models. The device transmits a message that includes the first set of parameters and at least one second set of parameters to another device, such as a user equipment (UE). In variations, the other device requests the second set of parameters and / or both the first set of parameters and the second set of parameters.

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