David Eppstein

TL;DR: Improving on a recent breakthrough of Sharir, this work shows how to find two circular disks of minimum radius covering a set of points in the Euclidean plane, in randomized expected time O(n log^2 n).

TL;DR: A new method for finding several types of optimalk-point sets, minimizing perimeter, diameter, circumradius, and related measures, by testing sets of theO(k) nearest neighbors to each point, which is better in a number of ways than previous algorithms, which were based on high-order Voronoi diagrams.

TL;DR: In this paper, an edge-ordered dynamic tree (EDDT) data structure is proposed for maintaining a minimum spanning forest of a plane graph subject to on-line modifications, such as changes in the edge weights and insertion and deletion of edges and vertices which are consistent with the given embedding.

TL;DR: In this paper, the authors developed data structures for dynamic closest pair problems with arbitrary distance functions, that do not necessarily come from any geometric structure on the objects, and applied these data structures to hierarchical clustering, greedy matching, and TSP heuristics, and discuss other potential applications in machine learning, Grobner bases, and local improvement algorithms.

TL;DR: In this paper, a technique called confluent drawing is used for visualizing non-planar graphs in a planar way, which allows groups of edges to be merged together and drawn as tracks.