A method for generating training data for a machine learning model comprising: accessing a plurality of output values of a machine learning model computed in response to a plurality of input data samples; analyzing the plurality of output values and the plurality of input data samples to compute a plurality of required data sample characteristics associated with at least one unsatisfactory output value of the plurality of output values; generating at least one new input data sample by providing a data generator with a plurality of generation constraints comprising the plurality of required data sample characteristics; and adding the at least one new input data sample to a data repository for producing training data for the machine learning model; wherein the at least one new input data sample comprises at least part of a simulated driving environment for training the machine learning model to operate in an autonomous automotive system.


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    Title :

    MACHINE LEARNING MODEL GENERALIZATION


    Contributors:

    Publication date :

    2024-11-28


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion



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