4 citations · 15 across the 6 of their papers we have counts for
7 papers
A statistical test for network similarity
Pierre Miasnikof, Alexander Y. Shetopaloff
In this article, we revisit and expand our prior work on graph similarity. As with our earlier work, we focus on a view of similarity which does not require node correspondence bet…
A clusterability test for directed graphs
Mario R. Guarracino, Pierre Miasnikof, Alexander Y. Shestopaloff +3
In this article, we extend a statistical test of graph clusterability, the test, to directed graphs with no self loops. The test, originally designed for undirected graphs,…
Graph clustering with Boltzmann machines
Pierre Miasnikof, Mohammad Bagherbeik, Ali Sheikholeslami
Graph clustering is the process of grouping vertices into densely connected sets called clusters. We tailor two mathematical programming formulations from the literature, to this p…
Market Graph Clustering Via QUBO and Digital Annealing
Seo Hong, Pierre Miasnikof, Roy Kwon +1
Our goal is to find representative nodes of a market graph that best replicate the returns of a broader market graph (index), a common task in the financial industry. We model our…
Graph Distances and Clustering
Pierre Miasnikof, Alexander Y. Shestopaloff, Leonidas Pitsoulis +1
With a view on graph clustering, we present a definition of vertex-to-vertex distance which is based on shared connectivity. We argue that vertices sharing more connections are clo…
Graph Clustering Via QUBO and Digital Annealing
Pierre Miasnikof, Seo Hong, Yuri Lawryshyn
This article empirically examines the computational cost of solving a known hard problem, graph clustering, using novel purpose-built computer hardware. We express the graph cluste…
A Statistical Density-Based Analysis of Graph Clustering Algorithm Performance
Pierre Miasnikof, Alexander Y. Shestopaloff, Anthony J. Bonner +2
Measuring graph clustering quality remains an open problem. To address it, we introduce quality measures based on comparisons of intra- and inter-cluster densities, an accompanying…