Dennis Rohde

activity

20182022

most citedRandom Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves

6 citations · 8 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CG2022

Stabbing balls with line segments and polygonal paths

Alexander Neuhaus, Dennis Rohde

We study the problem of ordered stabbing of $n$ balls (of arbitrary and possibly different radii, no ball contained in another) in $R^{d}$ , $d \geq 3$ , with either a directe…

cs.CG2022

Random projections for curves in high dimensions

Ioannis Psarros, Dennis Rohde

Modern time series analysis requires the ability to handle datasets that are inherently high-dimensional; examples include applications in climatology, where measurements from nume…

cs.CG2021

Approximating Length-Restricted Means under Dynamic Time Warping

Maike Buchin, Anne Driemel, Koen van Greevenbroek +2

We study variants of the mean problem under the $p$ -Dynamic Time Warping ( $p$ -DTW) distance, a popular and robust distance measure for sequential data. In our setting we are given…

cs.CG2021

Coresets for $(k, ℓ)$ -Median Clustering under the Fréchet Distance

Maike Buchin, Dennis Rohde

We present an algorithm for computing $ε$ -coresets for $(k, ℓ)$ -median clustering of polygonal curves in $R^{d}$ under the Fréchet distance. This type of clustering is an…

cs.CG2020

Approximating $(k, ℓ)$ -Median Clustering for Polygonal Curves

Maike Buchin, Anne Driemel, Dennis Rohde

In 2015, Driemel, Krivošija and Sohler introduced the $(k, ℓ)$ -median problem for clustering polygonal curves under the Fréchet distance. Given a set of input curves, the problem…

cs.LG2019★ 6 cited

Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves

Stefan Meintrup, Alexander Munteanu, Dennis Rohde

We study the $k$ -median clustering problem for high-dimensional polygonal curves with finite but unbounded number of vertices. We tackle the computational issue that arises from th…

cs.CG2019★ 2 cited

Coresets for $(k, l)$ -Clustering under the Fréchet Distance

Dennis Rohde

Clustering is the task of partitioning a given set of geometric objects. This is thoroughly studied when the objects are points in the euclidean space. There are also several appro…

cs.LG2018

A Theory-Based Evaluation of Nearest Neighbor Models Put Into Practice

Hendrik Fichtenberger, Dennis Rohde

In the $k$ -nearest neighborhood model ( $k$ -NN), we are given a set of points $P$ , and we shall answer queries $q$ by returning the $k$ nearest neighbors of $q$ in $P$ according to…