1 citations · 1 across the 1 of their papers we have counts for
4 papers
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…