From the 1 of 5 linked papers with an AI index.
5 papers
Connected Subspace Clustering: Hardness, a Scalable Heuristic, and an Application to Sea Level Geodesy
Johanna Hillebrand, Jan Höckendorff, Jürgen Kusche +5
Constrained optimization extends classical optimization by integrating side information, making it widely applicable across scientific and engineering domains. Consider a setting w…
A Fast and Simple -Approximation for Minimum Spanning Trees in Doubling Metrics
Jan Höckendorff, Jan Höckendorff, Felix Hommelsheim +2
The paper presents a deterministic algorithm that computes a (1+ε)-approximation of the minimum spanning tree in metric spaces with bounded doubling dimension, achieving a runtime…
Near Linear Time Approximation Schemes for Clustering of Partially Doubling Metrics
Anne Driemel, Jan Höckendorff, Ioannis Psarros +2
Given a finite metric space the -median problem is to find a set of centers that minimizes $\sum_{p\in X} \min_{c\in C} \mathbf{d}(p,c…
A near-linear time approximation scheme for -median clustering under discrete Fréchet distance
Anne Driemel, Jan Höckendorff, Ioannis Psarros +1
A time series of complexity is a sequence of real valued measurements. The discrete Fréchet distance is a distance measure between two time series and $y…
A Subquadratic Time Approximation Algorithm for Individually Fair k-Center
Matthijs Ebbens, Nicole Funk, Jan Höckendorff +2
We study the -center problem in the context of individual fairness. Let be a set of points in a metric space and be the distance between and its $\lceil…