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math.ST2026
Toward a Unified Statistical Theory of Multi-View Pretraining for Neural Knowledge Graph Learning
Jifan Zhang, Miklos Racz, Suqi Liu
Knowledge graph learning offers a powerful framework for representing and inferring structured knowledge, with broad practical applications. Two obstacles limit current methods: la…
math.ST2026
The statistical threshold for planted matchings and spanning trees
Louigi Addario-Berry, Omer Angel, Gábor Lugosi +2
In this paper, we study the problem of detecting the presence of a planted perfect matching or spanning tree in an Erdős--Rényi random graph. More precisely, we study the hypothesi…
math.ST2024
Harnessing Multiple Correlated Networks for Exact Community Recovery
Miklós Z. Rácz, Jifan Zhang
We study the problem of learning latent community structure from multiple correlated networks, focusing on edge-correlated stochastic block models with two balanced communities. Re…