1 citations · 1 across the 2 of their papers we have counts for
5 papers
Static to Dynamic Correlation Clustering
Nairen Cao, Vincent Cohen-Addad, Euiwoong Lee +7
Correlation clustering is a well-studied problem, first proposed by Bansal, Blum, and Chawla [Mach. Learn. '04]. The input is an unweighted, undirected graph. The problem is to clu…
Minimum Star Partitions of Simple Polygons in Polynomial Time
Mikkel Abrahamsen, Joakim Blikstad, André Nusser +1
We devise a polynomial-time algorithm for partitioning a simple polygon into a minimum number of star-shaped polygons. The question of whether such an algorithm exists has been…
Solving the Correlation Cluster LP in Sublinear Time
Nairen Cao, Vincent Cohen-Addad, Shi Li +7
Correlation Clustering is a fundamental and widely-studied problem in unsupervised learning and data mining. The input is a graph and the goal is to construct a clustering minimizi…
Bounding a Polygon by a Minimum Number of Vertices
Mikkel Abrahamsen, Jack Stade, Shuyi Yan +1
Suppose that a polygon is given as an array containing the vertices in counterclockwise order. We analyze how many vertices (including the index of each of these vertices) we n…
Combinatorial Correlation Clustering
Vincent Cohen-Addad, David Rasmussen Lolck, Marcin Pilipczuk +3
Correlation Clustering is a classic clustering objective arising in numerous machine learning and data mining applications. Given a graph , the goal is to partition the ve…