5 citations · 7 across the 4 of their papers we have counts for
6 papers
On seeded subgraph-to-subgraph matching: The ssSGM Algorithm and matchability information theory
Lingyao Meng, Mengqi Lou, Jianyu Lin +2
The subgraph-subgraph matching problem is, given a pair of graphs and a positive integer , to find vertices in the first graph, vertices in the second graph, and a bijec…
The Phantom Alignment Strength Conjecture: Practical use of graph matching alignment strength to indicate a meaningful graph match
Donniell E. Fishkind, Felix Parker, Hamilton Sawczuk +5
The alignment strength of a graph matching is a quantity that gives the practitioner a measure of the correlation of the two graphs, and it can also give the practitioner a sense f…
On a complete and sufficient statistic for the correlated Bernoulli random graph model
Donniell E. Fishkind, Avanti Athreya, Lingyao Meng +2
Inference on vertex-aligned graphs is of wide theoretical and practical importance.There are, however, few flexible and tractable statistical models for correlated graphs, and even…
Alignment Strength and Correlation for Graphs
Donniell E. Fishkind, Lingyao Meng, Ao Sun +2
When two graphs have a correlated Bernoulli distribution, we prove that the alignment strength of their natural bijection strongly converges to a novel measure of graph correlation…
Method for Computation of the Fisher Information Matrix in the Expectation-Maximization Algorithm
Lingyao Meng
The expectation-maximization (EM) algorithm is an iterative computational method to calculate the maximum likelihood estimators (MLEs) from the sample data. It converts a complicat…
Seeded Graph Matching
Donniell E. Fishkind, Sancar Adali, Heather G. Patsolic +4
Given two graphs, the graph matching problem is to align the two vertex sets so as to minimize the number of adjacency disagreements between the two graphs. The seeded graph matchi…