Improved Utility Analysis of Private CountSketch. (arXiv:2205.08397v1 [cs.DS])

Sketching is an important tool for dealing with high-dimensional vectors that
are sparse (or well-approximated by a sparse vector), especially useful in
distributed, parallel, and streaming settings. It is known that sketches can be
made differentially private by adding noise according to the sensitivity of the
sketch, and this has been used in private analytics and federated learning
settings. The post-processing property of differential privacy implies that all
estimates computed from the sketch can be released within the given privacy …

analysis ds