35 citations · 74 across the 13 of their papers we have counts for
17 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…
Connected k-Center and k-Diameter Clustering
Lukas Drexler, Jan Eube, Kelin Luo +4
Motivated by an application from geodesy, we introduce a novel clustering problem which is a -center (or k-diameter) problem with a side constraint. For the side constraint, we…
Coresets for constrained k-median and k-means clustering in low dimensional Euclidean space
Melanie Schmidt, Julian Wargalla
We study (Euclidean) -median and -means with constraints in the streaming model. There have been recent efforts to design unified algorithms to solve constrained -means pr…
Achieving anonymity via weak lower bound constraints for k-median and k-means
Anna Arutyunova, Melanie Schmidt
We study -clustering problems with lower bounds, including -median and -means clustering with lower bounds. In addition to the point set and the number of centers ,…
Noisy, Greedy and Not So Greedy k-means++
Anup Bhattacharya, Jan Eube, Heiko Röglin +1
The k-means++ algorithm due to Arthur and Vassilvitskii has become the most popular seeding method for Lloyd's algorithm. It samples the first center uniformly at random from the d…
Fully dynamic hierarchical diameter k-clustering and k-center
Melanie Schmidt, Christian Sohler
We develop dynamic data structures for maintaining a hierarchical k-center clustering when the points come from a discrete space . Our first data structure is for…