A trained model is constructed whose introduction cost is relatively low and that is robust to the difference in the attribute regarding acquisition of data. A learning apparatus according to one aspect of the invention executes, with respect to each learning data set, a first training step of training a second encoder and a second metadata identifier such that the identification result by the second metadata identifier matches the metadata, a second training step of training encoders and an estimator such that the result of estimation performed by the estimator matches correct answer data, a third training step of training a first metadata identifier such that the result of identification performed by the first metadata identifier matches the metadata, and a fourth training step of training a first encoder such that the result of identification performed by the first metadata identifier does not match the metadata. The third training step and the fourth training step are alternatingly and repeatedly executed.


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    Titel :

    LEARNING DEVICE, DEDUCTION DEVICE, DATA GENERATION DEVICE, LEARNING METHOD, AND LEARNING PROGRAM


    Weitere Titelangaben:

    LERNVORRICHTUNG, DEDUKTIONSVORRICHTUNG, DATENERZEUGUNGSVORRICHTUNG, LERNVERFAHREN UND LERNPROGRAMM
    DISPOSITIF D'APPRENTISSAGE, DISPOSITIF DE DÉDUCTION, DISPOSITIF DE GÉNÉRATION DE DONNÉES, PROCÉDÉ D'APPRENTISSAGE ET PROGRAMME D'APPRENTISSAGE


    Beteiligte:

    Erscheinungsdatum :

    21.12.2022


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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