From the 1 of 8 linked papers with an AI index.
8 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…
Time Series Decomposition using the Fréchet Distance
Anne Driemel, Jan Höckendorff, Ioannis Psarros +1
In this paper, we introduce a new data analysis problem that aims to decompose a set of univariate time series into a small set of base curves of length at most such that t…
Learning to Approximate Uniform Facility Location via Graph Neural Networks
Chendi Qian, Christopher Morris, Stefanie Jegelka +1
Neural networks, particularly message-passing neural networks (MPNNs), are increasingly used as heuristics for hard combinatorial optimization problems. Yet many learning-based met…
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…
Sublinear Algorithms for Estimating Single-Linkage Clustering Costs
Pan Peng, Christian Sohler, Yi Xu
Single-linkage clustering is a fundamental method for data analysis. Algorithmically, one can compute a single-linkage -clustering (a partition into clusters) by computing a…