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Related papers: Approximating Max-Cut under Graph-MSO Constraints

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MaxCut is a classical NP-complete problem and a crucial building block in many combinatorial algorithms. The famous Edwards-Erd\H{o}s bound states that any connected graph on n vertices with m edges contains a cut of size at least $m/2 +…

Data Structures and Algorithms · Computer Science 2024-07-02 Jonas Lill , Kalina Petrova , Simon Weber

A matching cut in a graph G is an edge cut of G that is also a matching. This short survey gives an overview of old and new results and open problems for Maximum Matching Cut, which is to determine the size of a largest matching cut in a…

Combinatorics · Mathematics 2023-12-21 Van Bang Le , Felicia Lucke , Daniël Paulusma , Bernard Ries

Interdiction problems ask about the worst-case impact of a limited change to an underlying optimization problem. They are a natural way to measure the robustness of a system, or to identify its weakest spots. Interdiction problems have been…

Optimization and Control · Mathematics 2015-11-10 Stephen R. Chestnut , Rico Zenklusen

For any $\varepsilon > 0$, we give a polynomial-time $n^\varepsilon$-approximation algorithm for Max Independent Set in graphs of bounded twin-width given with an $O(1)$-sequence. This result is derived from the following time-approximation…

Data Structures and Algorithms · Computer Science 2022-09-27 Pierre Bergé , Édouard Bonnet , Hugues Déprés , Rémi Watrigant

We study streaming algorithms for the maximum directed cut problem. The edges of an $n$-vertex directed graph arrive one by one in an arbitrary order, and the goal is to estimate the value of the maximum directed cut using a single pass and…

Data Structures and Algorithms · Computer Science 2026-04-01 Amir Azarmehr , Soheil Behnezhad , Shane Ferrante , Mohammad Saneian

Many combinatorial optimization problems can be phrased in the language of constraint satisfaction problems. We introduce a graph neural network architecture for solving such optimization problems. The architecture is generic; it works for…

Artificial Intelligence · Computer Science 2020-02-12 Jan Toenshoff , Martin Ritzert , Hinrikus Wolf , Martin Grohe

We approach the Max-3-Cut problem through the lens of maximizing complex-valued quadratic forms and demonstrate that low-rank structure in the objective matrix can be exploited, leading to alternative algorithms to classical semidefinite…

Data Structures and Algorithms · Computer Science 2026-04-27 Ria Stevens , Fangshuo Liao , Barbara Su , Jianqiang Li , Anastasios Kyrillidis

For an edge-weighted connected undirected graph, the minimum $k$-way cut problem is to find a subset of edges of minimum total weight whose removal separates the graph into $k$ connected components. The problem is NP-hard when $k$ is part…

Data Structures and Algorithms · Computer Science 2008-11-25 Mingyu Xiao , Leizhen Cai , Andrew C. Yao

The weighted MAX k-CUT problem consists of finding a k-partition of a given weighted undirected graph G(V,E) such that the sum of the weights of the crossing edges is maximized. The problem is of particular interest as it has a multitude of…

Quantum Physics · Physics 2024-11-22 Franz Georg Fuchs , Herman Øie Kolden , Niels Henrik Aase , Giorgio Sartor

The (non-uniform) sparsest cut problem is the following graph-partitioning problem: given a "supply" graph, and demands on pairs of vertices, delete some subset of supply edges to minimize the ratio of the supply edges cut to the total…

Data Structures and Algorithms · Computer Science 2021-06-01 Vincent Cohen-Addad , Anupam Gupta , Philip N. Klein , Jason Li

Can one reduce the size of a graph without significantly altering its basic properties? The graph reduction problem is hereby approached from the perspective of restricted spectral approximation, a modification of the spectral similarity…

Data Structures and Algorithms · Computer Science 2019-01-01 Andreas Loukas

In the $k$-cut problem, we want to find the lowest-weight set of edges whose deletion breaks a given (multi)graph into $k$ connected components. Algorithms of Karger \& Stein can solve this in roughly $O(n^{2k})$ time. On the other hand,…

Data Structures and Algorithms · Computer Science 2023-10-13 Anupam Gupta , David G. Harris , Euiwoong Lee , Jason Li

The maximum clique problem is a well known NP-Hard problem with applications in data mining, network analysis, informatics, and many other areas. Although there exist several algorithms with acceptable runtimes for certain classes of…

Data Structures and Algorithms · Computer Science 2012-11-15 Bharath Pattabiraman , Md. Mostofa Ali Patwary , Assefaw H. Gebremedhin , Wei-keng Liao , Alok Choudhary

We consider the classical minimum and maximum cut problems: find a partition of vertices of a graph into two disjoint subsets that minimize or maximize the sum of the weights of edges with endpoints in different subsets. It is known that if…

Combinatorics · Mathematics 2024-02-20 Andrei V. Nikolaev , Alexander V. Korostil

Kawarabayashi and Sidiropoulos [KS22] obtained an $O(\log^2 n)$-approximation algorithm for Multicut in planar digraphs via a natural LP relaxation, which also establishes a corresponding upper bound on the multicommodity flow-cut gap.…

Data Structures and Algorithms · Computer Science 2026-01-29 Chandra Chekuri , Rhea Jain

We address the following general question: given a graph class C on which we can solve Maximum Matching in (quasi) linear time, does the same hold true for the class of graphs that can be modularly decomposed into C ? A major difficulty in…

Data Structures and Algorithms · Computer Science 2018-04-26 Guillaume Ducoffe , Alexandru Popa

There are many applications of graph cuts in computer vision, e.g. segmentation. We present a novel method to reformulate the NP-hard, k-way graph partitioning problem as an approximate minimal s-t graph cut problem, for which a globally…

Computer Vision and Pattern Recognition · Computer Science 2009-07-02 Ghassan Hamarneh

Quantum algorithms for binary optimization problems have been the subject of extensive study. However, the application of quantum algorithms to integer optimization problems remains comparatively unexplored. In this paper, we study the…

Within the model-theoretic framework for supervised learning introduced by Grohe and Tur\'an (TOCS 2004), we study the parameterized complexity of learning concepts definable in monadic second-order logic (MSO). We show that the problem of…

Logic in Computer Science · Computer Science 2025-01-20 Steffen van Bergerem , Martin Grohe , Nina Runde

Although it has been claimed in two different papers that the maximum cardinality cut problem is polynomial-time solvable for proper interval graphs, both of them turned out to be erroneous. In this paper, we give FPT algorithms for the…

Data Structures and Algorithms · Computer Science 2020-06-09 Arman Boyacı , Tınaz Ekim , Mordechai Shalom