1 citations · 1 across the 5 of their papers we have counts for
5 papers
Toward a Unified Statistical Theory of Unsupervised Pretraining and Supervised Neural Knowledge Graph Learning
Jifan Zhang, Miklos Racz, Suqi Liu
Knowledge graph learning provides a powerful framework for representing and inferring structured knowledge, with broad practical applications. However, the scarcity of relation-spe…
Optimal Hardness of Online Algorithms for Large Common Induced Subgraphs
David Gamarnik, Miklós Z. Rácz, Gabe Schoenbach
We study the problem of efficiently finding large common induced subgraphs of two independent Erdős--Rényi random graphs . Recently, Chatterjee and…
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…
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…
Efficient Graph Matching for Correlated Stochastic Block Models
Shuwen Chai, Miklós Z. Rácz
We study learning problems on correlated stochastic block models with two balanced communities. Our main result gives the first efficient algorithm for graph matching in this setti…