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In this paper, we propose a graph classification approach for automatically determining whether to use a monolithic or a decomposition-based solution method. In this approach, an optimization problem is represented as a graph that captures…

Optimization and Control · Mathematics 2023-10-12 Ilias Mitrai , Prodromos Daoutidis

Expander decompositions of graphs have significantly advanced the understanding of many classical graph problems and led to numerous fundamental theoretical results. However, their adoption in practice has been hindered due to their…

Data Structures and Algorithms · Computer Science 2026-04-27 Kathrin Hanauer , Monika Henzinger , Robin Münk , Harald Räcke , Maximilian Vötsch

The complexity class NP of decision problems that can be solved nondeterministically in polynomial time is of great theoretical and practical importance where the notion of polynomial-time reductions between NP-problems is a key concept for…

Computational Complexity · Computer Science 2022-12-23 Hans-Jörg Kreowski , Sabine Kuske , Aaron Lye , Aljoscha Windhorst

Distributed computing excels at processing large scale data, but the communication cost for synchronizing the shared parameters may slow down the overall performance. Fortunately, the interactions between parameter and data in many problems…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-05-19 Mu Li , Dave G. Andersen , Alexander J. Smola

We study an extension of the classical graph cut problem, wherein we replace the modular (sum of edge weights) cost function by a submodular set function defined over graph edges. Special cases of this problem have appeared in different…

Data Structures and Algorithms · Computer Science 2016-03-29 Stefanie Jegelka , Jeff Bilmes

Graph isomorphism is an important computer science problem. The problem for the general case is unknown to be in polynomial time. The base algorithm for the general case works in quasi-polynomial time. The solutions in polynomial time for…

Discrete Mathematics · Computer Science 2017-11-23 Vaibhav Amit Patel

This paper proposes a framework that formulates a wide range of graph combinatorial optimization problems using permutation-based representations. These problems include the travelling salesman problem, maximum independent set, maximum cut,…

Artificial Intelligence · Computer Science 2024-10-23 Yimeng Min

In this paper, we introduce a graph matching method that can account for constraints of arbitrary order, with arbitrary potential functions. Unlike previous decomposition approaches that rely on the graph structures, we introduce a…

Computer Vision and Pattern Recognition · Computer Science 2018-02-26 D. Khuê Lê-Huu , Nikos Paragios

This paper addresses the problem of synchronizing orthogonal matrices over directed graphs. For synchronized transformations (or matrices), composite transformations over loops equal the identity. We formulate the synchronization problem as…

Optimization and Control · Mathematics 2017-04-10 Johan Thunberg , Florian Bernard , Jorge Goncalves

Time-varying graph signals are alternative representation of multivariate (or multichannel) signals in which a single time-series is associated with each of the nodes or vertex of a graph. Aided by the graph-theoretic tools, time-varying…

Signal Processing · Electrical Eng. & Systems 2023-01-10 Naveed ur Rehman

In the constraint programming framework, state-of-the-art static and dynamic decomposition techniques are hard to apply to problems with complete initial constraint graphs. For such problems, we propose a hybrid approach of these techniques…

Computational Complexity · Computer Science 2008-12-18 Stephane Zampelli , Martin Mann , Yves Deville , Rolf Backofen

Modular Decomposition focuses on repeatedly identifying a module M (a collection of vertices that shares exactly the same neighbourhood outside of M) and collapsing it into a single vertex. This notion of exactitude of neighbourhood is very…

Discrete Mathematics · Computer Science 2021-01-25 Michel Habib , Lalla Mouatadid , Eric Sopena , Mengchuan Zou

Graph-based semi-supervised learning usually involves two separate stages, constructing an affinity graph and then propagating labels for transductive inference on the graph. It is suboptimal to solve them independently, as the correlation…

Computer Vision and Pattern Recognition · Computer Science 2019-02-19 Qilin Li , Senjian An , Ling Li , Wanquan Liu

In this paper we introduce the 'simultaneous membership problem', defined for any graph class C characterized in terms of representations, e.g. any class of intersection graphs. Two graphs G_1 and G_2, sharing some vertices X (and the…

Discrete Mathematics · Computer Science 2008-11-26 Krishnam Raju Jampani , Anna Lubiw

A graph $G$ is said to be a `set graph' if it admits an acyclic orientation that is also `extensional', in the sense that the out-neighborhoods of its vertices are pairwise distinct. Equivalently, a set graph is the underlying graph of the…

Discrete Mathematics · Computer Science 2015-03-20 Martin Milanič , Romeo Rizzi , Alexandru I. Tomescu

Identifying the sets of operations that can be executed simultaneously is an important problem appearing in many parallel applications. By modeling the operations and their interactions as a graph, one can identify the independent…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-07-28 Ahmet Erdem Sarıyüce , Erik Saule , Ümit V. Çatalyürek

We study an analogue of the classical moment problem in the framework where moments are indexed by graphs instead of natural numbers. We study limit objects of graph sequences where edges are labeled by elements of a topological space.…

Combinatorics · Mathematics 2010-10-26 László Lovász , Balázs Szegedy

The main challenge addressed in this paper is to identify individual terms in a superposition of heat kernels on a graph. We establish geometric conditions on the vertices at which these heat kernels are centered and find bounds on the time…

Functional Analysis · Mathematics 2026-05-19 Bernhard G. Bodmann , Jennifer J. May

An emerging way of tackling the dimensionality issues arising in the modeling of a multivariate process is to assume that the inherent data structure can be captured by a graph. Nevertheless, though state-of-the-art graph-based methods have…

Machine Learning · Statistics 2016-07-13 Andreas Loukas , Nathanael Perraudin

Motivated by the need to extract meaning from large amounts of complex structured data, we consider three critical problems on graphs: localization, decomposition, and dictionary learning of piecewise-constant signals. These graph-based…

Social and Information Networks · Computer Science 2017-02-21 Siheng Chen , Yaoqing Yang , José. M. F. Moura , Jelena Kovačević