View source for 18013328. Fully Private Ensembles Using Knowledge Transfer (Google LLC)

=Fully Private Ensembles Using Knowledge Transfer=


==Organization Name==

[[:Category:Google LLC|Google LLC]]


[[Category:Google LLC]]

==Inventor(s)==

[[:Category:Preston Wooju Lee of Bellevue WA US|Preston Wooju Lee of Bellevue WA US]][[Category:Preston Wooju Lee of Bellevue WA US]]

==Fully Private Ensembles Using Knowledge Transfer==


This abstract first appeared for US patent application 18013328 titled 'Fully Private Ensembles Using Knowledge Transfer

==Original Abstract Submitted==

Example embodiments of the present disclosure provide for an example method including obtaining a private dataset. The example method includes dividing the private dataset into a first data subset and a second data subset. The example method includes training a first teacher model using the first data subset and a second teacher model using the second data subset. The example method includes generating the aggregate teacher model based at least in part on the trained first teacher model and the trained second teacher model. The example method can include obtaining a modified dataset that was generated based on a private dataset and labeling the modified dataset by the aggregate teacher model. The example method can include training a publicly available student model using the labeled modified dataset.



[[Category:G06N20/20]]
[[Category:CPC_G06N20/20]]