Adding a fingerprint to a machine learning model

Various embodiments relate to a method of producing a machine learning model with a fingerprint that maps an input value to an output label, including: selecting a set of extra input values, wherein the set of extra input values does not intersect with a set of training labeled input values for the...

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Bibliographische Detailangaben
Hauptverfasser: Derks, Gerardus Antonius Franciscus, Michiels, Wilhelmus Petrus Adrianus Johannus, Vauclair, Marc, Veshchikov, Nikita
Format: Patent
Sprache:eng
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Zusammenfassung:Various embodiments relate to a method of producing a machine learning model with a fingerprint that maps an input value to an output label, including: selecting a set of extra input values, wherein the set of extra input values does not intersect with a set of training labeled input values for the machine learning model; selecting a first set of artificially encoded output label values corresponding to each of the extra input values in the set of extra input values, wherein the first set of artificially encoded output label values are selected to indicate the fingerprint of a first machine learning model; and training the machine learning model using a combination of the extra input values with associated first set of artificially encoded output values and the set of training labeled input values to produce the first learning model with the fingerprint.