1 citations · 2 across the 7 of their papers we have counts for
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Structural Optimal Jacobian Accumulation and Minimum Edge Count are NP-Complete Under Vertex Elimination
Matthias Bentert, Alex Crane, Pål Grønås Drange +2
We study graph-theoretic formulations of two fundamental problems in algorithmic differentiation. The first (Structural Optimal Jacobian Accumulation) is that of computing a Jacobi…
Equalizing Closeness Centralities via Edge Additions
Alex Crane, Sorelle A. Friedler, Mihir Patel +3
Graph modification problems with the goal of optimizing some measure of a given node's network position have a rich history in the algorithms literature. Less commonly explored are…
Edge-Colored Clustering in Hypergraphs: Beyond Minimizing Unsatisfied Edges
Alex Crane, Thomas Stanley, Blair D. Sullivan +1
We consider a framework for clustering edge-colored hypergraphs, where the goal is to cluster (equivalently, to color) objects based on the primary type of multiway interactions th…
Optimizing Probabilistic Propagation in Graphs by Adding Edges
Aditya Bhaskara, Alex Crane, Shweta Jain +3
Probabilistic graphs are an abstraction that allow us to study randomized propagation in graphs. In a probabilistic graph, each edge is "active" with a certain probability, indepen…
Correlation Clustering with Vertex Splitting
Matthias Bentert, Alex Crane, Pål Grønås Drange +2
We explore Cluster Editing and its generalization Correlation Clustering with a new operation called permissive vertex splitting which addresses finding overlapping clusters in the…
Overlapping and Robust Edge-Colored Clustering in Hypergraphs
Alex Crane, Brian Lavallee, Blair D. Sullivan +1
A recent trend in data mining has explored (hyper)graph clustering algorithms for data with categorical relationship types. Such algorithms have applications in the analysis of soc…