activity
20222026
most citedOn the adversarial robustness of Locality-Sensitive Hashing in Hamming space

1 citations · 1 across the 8 of their papers we have counts for

collaborators

10 papers

cs.LG2026

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…

cs.DS2026

A Fast and Simple -Approximation for Minimum Spanning Trees in Doubling Metrics

Jan Höckendorff, Felix Hommelsheim, Christian Sohler +1

The minimum spanning tree (MST) problem is one of the most basic optimization problems on metric spaces and graphs. We study the problem of computing a -approximation to the…

cs.DS2026

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…

cs.DS2026

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…

cs.LG2026

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…

cs.DS2025

Sublinear Algorithms for Estimating Single-Linkage Clustering Costs

Pan Peng, Christian Sohler, Yi Xu

Single-linkage clustering (SLC) is a fundamental method for hierarchical data analysis. In the distance setting, a -clustering produced by SLC can be obtained by computing a min…

cs.DS2025

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 …

cs.DS2024

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…

cs.DS2024★ 1 cited

On the adversarial robustness of Locality-Sensitive Hashing in Hamming space

Michael Kapralov, Mikhail Makarov, Christian Sohler

Locality-sensitive hashing~[Indyk,Motwani'98] is a classical data structure for approximate nearest neighbor search. It allows, after a close to linear time preprocessing of the in…

cs.DS2022

Motif Cut Sparsifiers

Michael Kapralov, Mikhail Makarov, Sandeep Silwal +2

A motif is a frequently occurring subgraph of a given directed or undirected graph . Motifs capture higher order organizational structure of beyond edge relationships, and,…