3 papers
stat.ME2026
Leave-One-Out Neighborhood Smoothing for Graphons: Berry-Esseen Bounds, Confidence Intervals, and Honest Tuning
Behzad Aalipur, Rachel Kilby
Neighborhood smoothing methods achieve minimax-optimal rates for estimating edge probabilities under graphon models, but their use for statistical inference has remained limited. T…
math.PR2026
Distributional Limits for Eigenvalues of Graphon Kernel Matrices
Behzad Aalipur
We study the fluctuation behavior of individual eigenvalues of kernel matrices arising from dense graphon-based random graphs. Under minimal integrability and boundedness assumptio…
stat.ML2026
Perfect Clustering for Sparse Directed Stochastic Block Models
Behzad Aalipur, Yichen Qin
Exact recovery in stochastic block models (SBMs) is well understood in undirected settings, but remains considerably less developed for directed and sparse networks, particularly w…