8 citations · 19 across the 5 of their papers we have counts for
8 papers
Multidimensional Scaling: Approximation and Complexity
Erik Demaine, Adam Hesterberg, Frederic Koehler +2
Metric Multidimensional scaling (MDS) is a classical method for generating meaningful (non-linear) low-dimensional embeddings of high-dimensional data. MDS has a long history in th…
Maximum spread of graphs and bipartite graphs
Jane Breen, Alex W. N. Riasanovsky, Michael Tait +1
Given any graph , the (adjacency) spread of is the maximum absolute difference between any two eigenvalues of the adjacency matrix of . In this paper, we resolve a pair o…
Regarding two conjectures on clique and biclique partitions
Dhruv Rohatgi, John C. Urschel, Jake Wellens
For a graph , let denote the minimum number of cliques of needed to cover the edges of exactly once. Similarly, let denote the minimum number of bicliq…
Uniform Error Estimates for the Lanczos Method
John C. Urschel
The Lanczos method is one of the most powerful and fundamental techniques for solving an extremal symmetric eigenvalue problem. Convergence-based error estimates depend heavily on…
Discrete Trace Theorems and Energy Minimizing Spring Embeddings of Planar Graphs
John C. Urschel, Ludmil T. Zikatanov
Tutte's spring embedding theorem states that, for a three-connected planar graph, if the outer face of the graph is fixed as the complement of some convex region in the plane, and…
Testing Gap k-planarity is NP-complete
John C. Urschel, Jake Wellens
For all , we show that deciding whether a graph is -planar is NP-complete, extending the well-known fact that deciding 1-planarity is NP-complete. Furthermore, we show…