Privacy of the last iterate in cyclically-sampled DP-SGD on nonconvex composite losses

Weiwei Kong, Mónica Ribero

Differentially-private stochastic gradient descent (DP-SGD) is a family of iterative machine learning training algorithms that privatize gradients to generate a sequence of differe…