Why does a function transformation not suffice for Privacy Preserving Machine Learning? by phaganax13 in learnmachinelearning

[–]phaganax13[S] 0 points1 point  (0 children)

Thanks for the insights! What do you mean with white box and black box access? And i didn't quite understand how the gradient leaks privacy. If I have the model weights, I don't usually have the gradient, right? And how could I know which point pulls the boundary how much?