3 papers
math.ST2026
Exact recovery for seeded graph matching
Nicolas Fraiman, Michael Nisenzon
We study graph matching between two correlated networks in the almost fully seeded regime, where all but a vanishing fraction of vertex correspondences are revealed. Concretely, we…
math.ST2024
Semi-Supervised Community Detection via Quasi-Stationary Distributions
Nicolas Fraiman, Michael Nisenzon
Spectral clustering is a widely used method for community detection in networks. We focus on a semi-supervised community detection scenario in the Partially Labeled Stochastic Bloc…
math.NA2022
Splitting Circle Overview
Michael Nisenzon
This paper derives numerical bounds for and implements the splitting circle method for finding roots of a univariate polynomial in the presence of fixed precision.