We can apply the same distributed algorithms also for DP variational inference Jälkö et al . ( 2016 ) ; Park et al . ( 2016 ) . These methods rely on possibly clipped gradients or expected sufficient statistics calculated from the data . Typically , each training iteration would use only a mini - batch instead of the full data .