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In the {\sc Cluster Deletion} problem the goal is to remove the minimum number of edges of a given graph, such that every connected component of the resulting graph constitutes a clique. It is known that the decision version of {\sc Cluster…

Data Structures and Algorithms · Computer Science 2019-04-23 Athanasios L. Konstantinidis , Charis Papadopoulos

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. In this paper, we engineer the fastest known exact algorithm for the problem.…

Data Structures and Algorithms · Computer Science 2018-08-17 Monika Henzinger , Alexander Noe , Christian Schulz

We study graphons as a non-parametric generalization of stochastic block models, and show how to obtain compactly represented estimators for sparse networks in this framework. Our algorithms and analysis go beyond previous work in several…

Statistics Theory · Mathematics 2016-02-25 Christian Borgs , Jennifer T. Chayes , Henry Cohn , Shirshendu Ganguly

We consider the problem of maintaining an approximate maximum integral matching in a dynamic graph $G$, while the adversary makes changes to the edges of the graph. The goal is to maintain a $(1+\epsilon)$-approximate maximum matching for…

Data Structures and Algorithms · Computer Science 2022-07-07 Sepehr Assadi , Aaron Bernstein , Aditi Dudeja

The sparsest cut problem consists of identifying a small set of edges that breaks the graph into balanced sets of vertices. The normalized cut problem balances the total degree, instead of the size, of the resulting sets. Applications of…

Social and Information Networks · Computer Science 2017-02-17 Arlei Silva , Ambuj Singh , Ananthram Swami

Spectral graph theory is well known and widely used in computer vision. In this paper, we analyze image segmentation algorithms that are based on spectral graph theory, e.g., normalized cut, and show that there is a natural connection…

Computer Vision and Pattern Recognition · Computer Science 2016-11-09 Chengxi Ye , Yuxu Lin , Mingli Song , Chun Chen , David W. Jacobs

In this paper, we propose a path following replicator dynamic, and investigate its potentials in uncovering the underlying cluster structure of a graph. The proposed dynamic is a generalization of the discrete replicator dynamic. The…

Machine Learning · Computer Science 2013-03-12 Hairong Liu , Longin Jan Latecki , Shuicheng Yan

This paper proposes an improved quasi-Newton penalty decomposition algorithm for the minimization of continuously differentiable functions, possibly nonconvex, over sparse symmetric sets. The method solves a sequence of penalty subproblems…

Optimization and Control · Mathematics 2026-01-21 Ahmad Mousavi , Morteza Kimiaei , Saman Babaie-Kafaki , Vyacheslav Kungurtsev

In recent years, the expander decomposition method was used to develop many graph algorithms, resulting in major improvements to longstanding complexity barriers. This powerful hammer has led the community to (1) believe that most problems…

Data Structures and Algorithms · Computer Science 2022-11-28 Amir Abboud , Nathan Wallheimer

We present an on-line algorithm for maintaining a topological order of a directed acyclic graph as arcs are added, and detecting a cycle when one is created. Our algorithm takes O(m^{1/2}) amortized time per arc, where m is the total number…

Data Structures and Algorithms · Computer Science 2008-03-07 Bernhard Haeupler , Siddhartha Sen , Robert E. Tarjan

Graph Sparsification aims at compressing large graphs into smaller ones while preserving important characteristics of the input graph. In this work we study Vertex Sparsifiers, i.e., sparsifiers whose goal is to reduce the number of…

Data Structures and Algorithms · Computer Science 2017-12-29 Gramoz Goranci , Monika Henzinger , Pan Peng

Cuts in graphs are a fundamental object of study, and play a central role in the study of graph algorithms. The problem of sparsifying a graph while approximately preserving its cut structure has been extensively studied and has many…

Data Structures and Algorithms · Computer Science 2020-09-11 Yu Chen , Sanjeev Khanna , Ansh Nagda

Computing the edge expansion of a graph is a famously hard combinatorial problem for which there have been many approximation studies. We present two variants of exact algorithms using semidefinite programming (SDP) to compute this constant…

Optimization and Control · Mathematics 2025-11-26 Akshay Gupte , Melanie Siebenhofer , Angelika Wiegele

This paper bridges discrete and continuous optimization approaches for decomposable submodular function minimization, in both the standard and parametric settings. We provide improved running times for this problem by reducing it to a…

Data Structures and Algorithms · Computer Science 2021-03-08 Kyriakos Axiotis , Adam Karczmarz , Anish Mukherjee , Piotr Sankowski , Adrian Vladu

A recent paper by Abboud and Wallheimer [ITCS 2023] presents self-reductions for various fundamental graph problems, which transform worst-case instances to expanders, thus proving that the complexity remains unchanged if the input is…

Data Structures and Algorithms · Computer Science 2024-07-02 Amir Abboud , Nathan Wallheimer

Finding maximum cliques in large networks is a challenging combinatorial problem with many real-world applications. We present a fast algorithm to achieve the exact solution for the maximum clique problem in large sparse networks based on…

Social and Information Networks · Computer Science 2024-04-22 Tianlong Fan , Wenjun Jiang , Yi-Cheng Zhang , Linyuan Lü

The slice decomposition is a bijective method for enumerating planar maps (graphs embedded in the sphere) with control over face degrees. In this paper, we extend the slice decomposition to the richer setting of hypermaps, naturally…

Combinatorics · Mathematics 2026-04-29 Marie Albenque , Jérémie Bouttier

In this paper, we revisit the split decomposition of graphs and give new combinatorial and algorithmic results for the class of totally decomposable graphs, also known as the distance hereditary graphs, and for two non-trivial subclasses,…

Discrete Mathematics · Computer Science 2011-04-19 Emeric Gioan , Christophe Paul

Lifelong SLAM considers long-term operation of a robot where already mapped locations are revisited many times in changing environments. As a result, traditional graph-based SLAM approaches eventually become extremely slow due to the…

Robotics · Computer Science 2021-10-05 Gerhard Kurz , Matthias Holoch , Peter Biber

In this work, we present the first algorithm to compute expander decompositions in an m-edge directed graph with near-optimal time \~O(m). Further, our algorithm can maintain such a decomposition in a dynamic graph and again obtains…

Data Structures and Algorithms · Computer Science 2025-02-12 Aurelio L. Sulser , Maximilian Probst Gutenberg