27 citations · 100 across the 31 of their papers we have counts for
6 papers · 1 filter
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…
Structural Rounding: Approximation Algorithms for Graphs Near an Algorithmically Tractable Class
Erik D. Demaine, Timothy D. Goodrich, Kyle Kloster +5
We develop a new framework for generalizing approximation algorithms from the structural graph algorithm literature so that they apply to graphs somewhat close to that class (a sce…
An Updated Experimental Evaluation of Graph Bipartization Methods
Timothy D. Goodrich, Eric Horton, Blair D. Sullivan
We experimentally evaluate the practical state-of-the-art in graph bipartization (Odd Cycle Transversal), motivated by recent advances in near-term quantum computing hardware and t…
Subgraph centrality and walk-regularity
Eric Horton, Kyle Kloster, Blair D. Sullivan
Matrix-based centrality measures have enjoyed significant popularity in network analysis, in no small part due to our ability to rigorously analyze their behavior as parameters var…
Polynomial Treedepth Bounds in Linear Colorings
Jeremy Kun, Michael P. O'Brien, Marcin Pilipczuk +1
Low-treedepth colorings are an important tool for algorithms that exploit structure in classes of bounded expansion; they guarantee subgraphs that use few colors have bounded treed…