Edge-flipping a generalized random dot-product graph produces another such graph in one higher dimension, and a privacy-adjusted spectral embedding consistently recovers latent positions and persistence diagrams at near-minimax rates.
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Signal Recovery from Random Dot-Product Graphs Under Local Differential Privacy
Edge-flipping a generalized random dot-product graph produces another such graph in one higher dimension, and a privacy-adjusted spectral embedding consistently recovers latent positions and persistence diagrams at near-minimax rates.