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US 2021/0065040 A1Published application
Sensitivity in supervised machine learning with experience data
AssigneeSap SE
InventorsPeter Eberlein, Volker Driesen
Life of this patent
Estimating the term…
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AssigneeSap SE
InventorsPeter Eberlein, Volker Driesen
Estimating the term…
In an example embodiment, a process is introduced into a machine learned model where additional results are output by the machine learned model in addition to those results that would be obtained through use of the trained model itself. In some example embodiments, these additional results may be random or semi-random to introduce results that might otherwise not have been recommended by the machine learned model. By introducing such additional results in a controlled way, it becomes possible to reduce biases caused by a self-reinforcing feedback loop while still presenting users with accurate machine learned model results.
A system comprising:
A method comprising:
A non-transitory machine-readable medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform operations comprising:
Dependencies are inferred from the claim text.