activity
20142026
most citedThe Computational Complexity of ReLU Network Training Parameterized by Data Dimensionality

19 citations · 118 across the 26 of their papers we have counts for

collaborators

38 papers

cs.DS2026

Parameterizing Cluster Editing by the Number of Deletions

Vincent Froese, Leon Kellerhals, Frank Sommer +2

In Cluster Editing, we are given a graph and an integer and ask whether at most edge insertions and deletions turn into a disjoint union of cliques. Komusiewicz and…

cs.DS2026

Parameterized Complexity of Temporal Agony

Tom-Lukas Breitkopf, Vincent Froese, Anton Herrmann +1

Real-world networks are often organized in several layers forming a hierarchy which determines the interaction between the individual components. In order to discover such hierarch…

cs.DS2026

Computational Complexity of the Interval Ordering Problem

Simeon Pawlowski, Vincent Froese

We study an interval ordering problem introduced by Dürr et al. [Discrete Appl. Math. 2012] which is motivated by applications in bioinformatics. The task is to order a given set o…

cs.DS2026

Parameterized Algorithms for Computing MAD Trees

Tom-Lukas Breitkopf, Vincent Froese, Anton Herrmann +2

We consider the well-studied problem of finding a spanning tree with minimum average distance between vertex pairs (called a MAD tree). This is a classic network design problem whi…

cs.DS2026

Density Matters: A Complexity Dichotomy of Deleting Edges to Bound Subgraph Density

Matthias Bentert, Tom-Lukas Breitkopf, Vincent Froese +2

We study -Bounded-Density Edge Deletion (-BDED), where given an undirected graph , the task is to remove as few edges as possible to obtain a graph where no subgraph…

cs.GT2024

Nash Equilibria in Reverse Temporal Voronoi Games

Simeon Pawlowski, Vincent Froese

We study Voronoi games on temporal graphs as introduced by Boehmer et al. (IJCAI 2021) where two players each select a vertex in a temporal graph with the goal of reaching the othe…

cs.CC2023★ 4 cited

Training Neural Networks is NP-Hard in Fixed Dimension

Vincent Froese, Christoph Hertrich

We study the parameterized complexity of training two-layer neural networks with respect to the dimension of the input data and the number of hidden neurons, considering ReLU and l…

math.CO2022

Terrain-like Graphs and the Median Genocchi Numbers

Vincent Froese, Malte Renken

A graph with vertex set is terrain-like if, for any edge pair with , the edge also exists. Terrain-like graphs frequently appe…

cs.DS2022

There and Back Again: On Applying Data Reduction Rules by Undoing Others

Aleksander Figiel, Vincent Froese, André Nichterlein +1

Data reduction rules are an established method in the algorithmic toolbox for tackling computationally challenging problems. A data reduction rule is a polynomial-time algorithm th…

cs.DS2022

Disentangling the Computational Complexity of Network Untangling

Vincent Froese, Pascal Kunz, Philipp Zschoche

We study the network untangling problem introduced by Rozenshtein, Tatti, and Gionis [DMKD 2021], which is a variant of Vertex Cover on temporal graphs -- graphs whose edge set cha…

cs.DS2021★ 1 cited

Modification-Fair Cluster Editing

Vincent Froese, Leon Kellerhals, Rolf Niedermeier

The classic Cluster Editing problem (also known as Correlation Clustering) asks to transform a given graph into a disjoint union of cliques (clusters) by a small number of edge mod…

cs.LG2021★ 19 cited

The Computational Complexity of ReLU Network Training Parameterized by Data Dimensionality

Vincent Froese, Christoph Hertrich, Rolf Niedermeier

Understanding the computational complexity of training simple neural networks with rectified linear units (ReLUs) has recently been a subject of intensive research. Closing gaps an…

cs.GT2021★ 2 cited

Equilibria in Schelling Games: Computational Hardness and Robustness

Luca Kreisel, Niclas Boehmer, Vincent Froese +1

In the simplest game-theoretic formulation of Schelling's model of segregation on graphs, agents of two different types each select their own vertex in a given graph so as to maxim…

cs.GT2021

Two Influence Maximization Games on Graphs Made Temporal

Niclas Boehmer, Vincent Froese, Julia Henkel +3

To address the dynamic nature of real-world networks, we generalize competitive diffusion games and Voronoi games from static to temporal graphs, where edges may appear or disappea…

cs.DM2020★ 3 cited

Parameterized Algorithms for Matrix Completion With Radius Constraints

Tomohiro Koana, Vincent Froese, Rolf Niedermeier

Considering matrices with missing entries, we study NP-hard matrix completion problems where the resulting completed matrix shall have limited (local) radius. In the pure radius ve…

cs.DM2020★ 1 cited

Faster Binary Mean Computation Under Dynamic Time Warping

Nathan Schaar, Vincent Froese, Rolf Niedermeier

Many consensus string problems are based on Hamming distance. We replace Hamming distance by the more flexible (e.g., easily coping with different input string lengths) dynamic tim…

cs.DS2020

The Complexity of Binary Matrix Completion Under Diameter Constraints

Tomohiro Koana, Vincent Froese, Rolf Niedermeier

We thoroughly study a novel but basic combinatorial matrix completion problem: Given a binary incomplete matrix, fill in the missing entries so that every pair of rows in the resul…

math.OC2019

Mathematical Programming Models for Mean Computation in Dynamic Time Warping Spaces

Vincent Froese, Christoph Hansknecht

The dynamic time warping (dtw) distance is an established tool for mining time series data. The DTW-Mean problem consists of computing a series which minimizes the so-called Fréche…

cs.DM2019★ 3 cited

Persistent Graphs and Cyclic Polytope Triangulations

Vincent Froese, Malte Renken

We prove a bijection between the triangulations of the 3-dimensional cyclic polytope C(n+2, 3) and persistent graphs with n vertices. We show that under this bijection the Stasheff…

cs.DS2019

An Average-Compress Algorithm for the Sample Mean Problem under Dynamic Time Warping

Brijnesh Jain, Vincent Froese, David Schultz

Computing a sample mean of time series under dynamic time warping (DTW) is NP-hard. Consequently, there is an ongoing research effort to devise efficient heuristics. The majority o…

cs.DS2019

Good Things Come to Those Who Swap Objects on Paths

Matthias Bentert, Jiehua Chen, Vincent Froese +1

We study a simple exchange market, introduced by Gourvés, Lesca and Wilczynski (IJCAI-17), where every agent initially holds a single object. The agents have preferences over the o…

cs.CG2019★ 4 cited

Advancing Through Terrains

Vincent Froese, Malte Renken

We study terrain visibility graphs, a well-known graph class closely related to polygon visibility graphs in computational geometry, for which a precise graph-theoretical character…

cs.DS2019

Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series

Vincent Froese, Brijnesh Jain, Maciej Rymar +1

Dynamic Time Warping (DTW) is a well-known similarity measure for time series. The standard dynamic programming approach to compute the DTW distance of two length- time series,…

cs.LG2018★ 5 cited

Comparing Temporal Graphs Using Dynamic Time Warping

Vincent Froese, Brijnesh Jain, Rolf Niedermeier +1

Within many real-world networks the links between pairs of nodes change over time. Thus, there has been a recent boom in studying temporal graphs. Recognizing patterns in temporal…