20 citations · 35 across the 9 of their papers we have counts for
17 papers
Parameterized algorithms for identifying gene co-expression modules via weighted clique decomposition
Madison Cooley, Casey S. Greene, Davis Issac +2
We present a new combinatorial model for identifying regulatory modules in gene co-expression data using a decomposition into weighted cliques. To capture complex interaction effec…
A color-avoiding approach to subgraph counting in bounded expansion classes
Felix Reidl, Blair D. Sullivan
We present an algorithm to count the number of occurrences of a pattern graph as an induced subgraph in a host graph . If belongs to a bounded expansion class, the algor…
Approximating Vertex Cover using Structural Rounding
Brian Lavallee, Hayley Russell, Blair D. Sullivan +1
In this work, we provide the first practical evaluation of the structural rounding framework for approximation algorithms. Structural rounding works by first editing to a well-stru…
Faster Biclique Mining in Near-Bipartite Graphs
Blair D. Sullivan, Andrew van der Poel, Trey Woodlief
Identifying dense bipartite subgraphs is a common graph data mining task. Many applications focus on the enumeration of all maximal bicliques (MBs), though sometimes the stricter v…
Mining Maximal Induced Bicliques using Odd Cycle Transversals
Kyle Kloster, Blair D. Sullivan, Andrew van der Poel
Many common graph data mining tasks take the form of identifying dense subgraphs (e.g. clustering, clique-finding, etc). In biological applications, the natural model for these den…
Benchmarking treewidth as a practical component of tensor-network--based quantum simulation
Eugene F. Dumitrescu, Allison L. Fisher, Timothy D. Goodrich +3
Tensor networks are powerful factorization techniques which reduce resource requirements for numerically simulating principal quantum many-body systems and algorithms. The computat…