no code implementations • 1 Feb 2023 • Roman Erhardt, Kathrin Hanauer, Nils Kriege, Christian Schulz, Darren Strash

We propose improved exact and heuristic algorithms for solving the maximum weight clique problem, a well-known problem in graph theory with many applications.

1 code implementation • 15 Dec 2022 • Jonas Ammeling, Lars-Henning Schmidt, Jonathan Ganz, Tanja Niedermair, Christoph Brochhausen-Delius, Christian Schulz, Katharina Breininger, Marc Aubreville

Attention-based multiple instance learning (AMIL) algorithms have proven to be successful in utilizing gigapixel whole-slide images (WSIs) for a variety of different computational pathology tasks such as outcome prediction and cancer subtyping problems.

no code implementations • 26 May 2022 • Ümit V. Çatalyürek, Karen D. Devine, Marcelo Fonseca Faraj, Lars Gottesbüren, Tobias Heuer, Henning Meyerhenke, Peter Sanders, Sebastian Schlag, Christian Schulz, Daniel Seemaier, Dorothea Wagner

In recent years, significant advances have been made in the design and evaluation of balanced (hyper)graph partitioning algorithms.

1 code implementation • 11 May 2022 • Adil Chhabra, Marcelo Fonseca Faraj, Christian Schulz

A widely-used operation on graphs is local clustering, i. e., extracting a well-characterized community around a seed node without the need to process the whole graph.

no code implementations • 19 Jan 2022 • Steve Ahlswede, Nimisha Thekke-Madam, Christian Schulz, Birgit Kleinschmit, Begüm Demir

The collection of a high number of pixel-based labeled training samples for tree species identification is time consuming and costly in operational forestry applications.

no code implementations • 22 Feb 2021 • Kathrin Hanauer, Monika Henzinger, Christian Schulz

In recent years, significant advances have been made in the design and analysis of fully dynamic algorithms.

Data Structures and Algorithms

1 code implementation • 18 Feb 2021 • Marcelo Fonseca Faraj, Christian Schulz

On the one hand, there are streaming algorithms that have been adopted to partition massive graph data on small machines.

graph partitioning Data Structures and Algorithms

no code implementations • 16 Feb 2021 • Philipp Hieronymi, Dun Ma, Reed Oei, Luke Schaeffer, Christian Schulz, Jeffrey Shallit

We show that the first-order theory of Sturmian words over Presburger arithmetic is decidable.

Logic in Computer Science Combinatorics Logic

1 code implementation • 13 Jan 2021 • Monika Henzinger, Alexander Noe, Christian Schulz

We present a practically efficient algorithm for maintaining a global minimum cut in large dynamic graphs under both edge insertions and deletions.

Data Structures and Algorithms

1 code implementation • 12 Aug 2020 • Alexander Gellner, Sebastian Lamm, Christian Schulz, Darren Strash, Bogdán Zaválnij

A key feature of our work is that some transformation rules can increase the size of the input.

1 code implementation • 19 May 2020 • Sascha Hunold, Konrad von Kirchbach, Markus Lehr, Christian Schulz, Jesper Larsson Träff

An extensive experimental evaluation on several HPC machines shows that our algorithms are up to two orders of magnitude faster in running time than a (sequential) high-quality general graph mapping tool, while obtaining similar results in communication performance.

Distributed, Parallel, and Cluster Computing

1 code implementation • 24 Apr 2020 • Monika Henzinger, Alexander Noe, Christian Schulz

We give an improved branch-and-bound solver for the multiterminal cut problem, based on the recent work of Henzinger et al.. We contribute new, highly effective data reduction rules to transform the graph into a smaller equivalent instance.

Data Structures and Algorithms Combinatorics

3 code implementations • 23 Apr 2020 • Wolfgang Ost, Christian Schulz, Darren Strash

Many applications rely on time-intensive matrix operations, such as factorization, which can be sped up significantly for large sparse matrices by interpreting the matrix as a sparse graph and computing a node ordering that minimizes the so-called fill-in.

Data Structures and Algorithms Combinatorics

1 code implementation • 17 Feb 2020 • Monika Henzinger, Alexander Noe, Christian Schulz, Darren Strash

We present a practically efficient algorithm that finds all global minimum cuts in huge undirected graphs.

Data Structures and Algorithms

no code implementations • 6 Feb 2020 • Merten Popp, Sebastian Schlag, Christian Schulz, Daniel Seemaier

The acyclic hypergraph partitioning problem is to partition the hypernodes of a directed acyclic hypergraph into a given number of blocks of roughly equal size such that the corresponding quotient graph is acyclic while minimizing an objective function on the partition.

no code implementations • 30 Nov 2019 • Christian Schulz

Designing and evaluating scalable graph algorithms to handle these data sets is a crucial task on the road to understanding the underlying systems.

no code implementations • 12 Aug 2019 • Monika Henzinger, Alexander Noe, Christian Schulz

We introduce the fastest known exact algorithm~for~the multiterminal cut problem with k terminals.

Data Structures and Algorithms Distributed, Parallel, and Cluster Computing

no code implementations • 20 Aug 2018 • Sebastian Schlag, Matthias Schmitt, Christian Schulz

The time complexity of support vector machines (SVMs) prohibits training on huge data sets with millions of data points.

2 code implementations • 16 Aug 2018 • Monika Henzinger, Alexander Noe, Christian Schulz

State-of-the-art algorithms like the algorithm of Padberg and Rinaldi or the algorithm of Nagamochi, Ono and Ibaraki identify edges that can be contracted to reduce the graph size such that at least one minimum cut is maintained in the contracted graph.

Data Structures and Algorithms

1 code implementation • 20 Feb 2018 • Sonja Biedermann, Monika Henzinger, Christian Schulz, Bernhard Schuster

It is common knowledge that there is no single best strategy for graph clustering, which justifies a plethora of existing approaches.

1 code implementation • 20 Oct 2017 • Daniel Funke, Sebastian Lamm, Peter Sanders, Christian Schulz, Darren Strash, Moritz von Looz

Analyzing massive complex networks yields promising insights about our everyday lives.

Distributed, Parallel, and Cluster Computing Data Structures and Algorithms Social and Information Networks

2 code implementations • GECCO 2018 2018 • Robin Andre, Sebastian Schlag, Christian Schulz

Hypergraph partitioning has a wide range of important applications such as VLSI design or scientific computing.

Data Structures and Algorithms

no code implementations • 25 Sep 2017 • Orlando Moreira, Merten Popp, Christian Schulz

Directed graphs are widely used to model data flow and execution dependencies in streaming applications.

2 code implementations • 21 Aug 2017 • Monika Henzinger, Alexander Noe, Christian Schulz, Darren Strash

The minimum cut problem for an undirected edge-weighted graph asks us to divide its set of nodes into two blocks while minimizing the weight sum of the cut edges.

Data Structures and Algorithms Distributed, Parallel, and Cluster Computing

no code implementations • 3 Apr 2017 • Orlando Moreira, Merten Popp, Christian Schulz

In this work, we show that this more constrained version of the graph partitioning problem is NP-complete and present heuristics that achieve a close approximation of the optimal solution found by an exhaustive search for small problem instances and much better scalability for larger instances.

1 code implementation • 6 Feb 2017 • Peter Sanders, Christian Schulz, Darren Strash, Robert Williger

Computing high quality node separators in large graphs is necessary for a variety of applications, ranging from divide-and-conquer algorithms to VLSI design.

1 code implementation • ALENEX 2016 2017 • Sebastian Schlag, Vitali Henne, Tobias Heuer, Henning Meyerhenke, Peter Sanders, Christian Schulz

We develop a multilevel algorithm for hypergraph partitioning that contracts the vertices one at a time.

Data Structures and Algorithms

1 code implementation • 2 Sep 2015 • Sebastian Lamm, Peter Sanders, Christian Schulz, Darren Strash, Renato F. Werneck

To avoid this problem, we recursively choose vertices that are likely to be in a large independent set (using an evolutionary approach), then further kernelize the graph.

1 code implementation • 4 May 2015 • Vitali Henne, Henning Meyerhenke, Peter Sanders, Sebastian Schlag, Christian Schulz

Using label propagation local search is several times faster than hMetis and gives better quality than PaToH for a VLSI benchmark set.

Data Structures and Algorithms G.2.2; D.1.4

no code implementations • 29 Apr 2015 • Nitin Ahuja, Matthias Bender, Peter Sanders, Christian Schulz, Andreas Wagner

Given a set of basic areas, the territory design problem asks to create a predefined number of territories, each containing at least one basic area, such that an objective function is optimized.

no code implementations • 5 Feb 2015 • Sebastian Lamm, Peter Sanders, Christian Schulz

The core innovations of the algorithm are very natural combine operations based on graph partitioning and local search algorithms.

1 code implementation • 18 Apr 2014 • Henning Meyerhenke, Peter Sanders, Christian Schulz

This paper addresses this problem by parallelizing and adapting the label propagation technique originally developed for graph clustering.

1 code implementation • 1 Oct 2012 • Peter Sanders, Christian Schulz

We present a novel local improvement scheme for the perfectly balanced graph partitioning problem.

1 code implementation • 3 Oct 2011 • Peter Sanders, Christian Schulz

We present a novel distributed evolutionary algorithm, KaFFPaE, to solve the Graph Partitioning Problem, which makes use of KaFFPa (Karlsruhe Fast Flow Partitioner).

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