6 papers
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…
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…
Equalizing Closeness Centralities via Edge Additions
Alex Crane, Sorelle A. Friedler, Mihir Patel +1
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…
A Space-Efficient Algebraic Approach to Robotic Motion Planning
Matthias Bentert, Daniel Coimbra Salomao, Alex Crane +3
We consider efficient route planning for robots in applications such as infrastructure inspection and automated surgical imaging. These tasks can be modeled via the combinatorial p…
Fast algorithms to improve fair information access in networks
Dennis Robert Windham, Caroline J. Wendt, Alex Crane +5
We consider the problem of selecting seed nodes in a network to maximize the minimum probability of activation under an independent cascade beginning at these seeds. The motiva…
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…