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We study the graph alignment problem over two independent Erd\H{o}s-R\'enyi graphs on $n$ vertices, with edge density $p$ falling into two regimes separated by the critical window around $p_c=\sqrt{\log n/n}$. Our result reveals an…

Probability · Mathematics 2025-03-27 Hang Du , Shuyang Gong , Rundong Huang

We provide CONGEST model algorithms for approximating minimum weighted vertex cover and the maximum weighted matching. For bipartite graphs, we show that a $(1+\varepsilon)$-approximate weighted vertex cover can be computed…

Data Structures and Algorithms · Computer Science 2023-08-09 Salwa Faour , Marc Fuchs , Fabian Kuhn

The Exact Matching (EM) problem asks whether there exists a perfect matching which uses a prescribed number of red edges in a red/blue edge-colored graph. While there exists a randomized polynomial-time algorithm for the problem, only some…

Data Structures and Algorithms · Computer Science 2025-10-15 Nicolas El Maalouly , Kostas Lakis

We study the problem of detecting the edge correlation between two random graphs with $n$ unlabeled nodes. This is formalized as a hypothesis testing problem, where under the null hypothesis, the two graphs are independently generated;…

Statistics Theory · Mathematics 2021-02-09 Yihong Wu , Jiaming Xu , Sophie H. Yu

For a $d$-uniform random hypergraph on $n$ vertices in which hyperedges are included i.i.d.\ so that the average degree in the hypergraph is $n^{\delta+o(1)}$, the projection of such a hypergraph is a graph on the same $n$ vertices where an…

Statistics Theory · Mathematics 2026-04-03 Shuyang Gong , Zhangsong Li , Qiheng Xu

We prove that there is a randomized polynomial-time algorithm that given an edge-weighted graph $G$ excluding a fixed-minor $Q$ on $n$ vertices and an accuracy parameter $\varepsilon>0$, constructs an edge-weighted graph~$H$ and an…

Data Structures and Algorithms · Computer Science 2023-04-17 Vincent Cohen-Addad , Hung Le , Marcin Pilipczuk , Michał Pilipczuk

Exact pattern matching in labeled graphs is the problem of searching paths of a graph $G=(V,E)$ that spell the same string as the pattern $P[1..m]$. This basic problem can be found at the heart of more complex operations on variation graphs…

Computational Complexity · Computer Science 2020-06-04 Massimo Equi , Roberto Grossi , Veli Mäkinen

Aligning a sequence to a walk in a labeled graph is a problem of fundamental importance to Computational Biology. For finding a walk in an arbitrary graph with $|E|$ edges that exactly matches a pattern of length $m$, a lower bound based on…

Data Structures and Algorithms · Computer Science 2022-02-01 Daniel Gibney , Sharma V. Thankachan , Srinivas Aluru

In this paper, we study the exact recovery problem in the Gaussian weighted version of the Stochastic block model with two symmetric communities. We provide the information-theoretic threshold in terms of the signal-to-noise ratio (SNR) of…

Statistics Theory · Mathematics 2024-02-21 Aaradhya Pandey , Sanjeev Kulkarni

We study the problem of connecting the parts of a multipartite graph using a minimum number of edges under a matching constraint. We introduce interconnection trees, defined as matchings whose projections onto the quotient graph form a…

Computational Complexity · Computer Science 2026-05-19 Noé Demange , Yann Strozecki

In this work, we consider the problem of recovery a planted $k$-densest sub-hypergraph on $d$-uniform hypergraphs. This fundamental problem appears in different contexts, e.g., community detection, average-case complexity, and neuroscience…

Machine Learning · Computer Science 2021-01-29 Luca Corinzia , Paolo Penna , Wojciech Szpankowski , Joachim M. Buhmann

In the problem (Unweighted) Max-Cut we are given a graph $G = (V,E)$ and asked for a set $S \subseteq V$ such that the number of edges from $S$ to $V \setminus S$ is maximal. In this paper we consider an even harder problem: (Weighted)…

Data Structures and Algorithms · Computer Science 2022-10-14 Hauke Brinkop , Klaus Jansen

This paper considers the problem of completing a rating matrix based on sub-sampled matrix entries as well as observed social graphs and hypergraphs. We show that there exists a \emph{sharp threshold} on the sample probability for the task…

Machine Learning · Computer Science 2026-05-29 Zhongtian Ma , Qiaosheng Zhang , Zhen Wang

We study set selection problems where the weights are uncertain. Instead of its exact weight, only an uncertainty interval containing its true weight is available for each element. In some cases, some solutions are universally optimal;…

Data Structures and Algorithms · Computer Science 2024-04-29 Christoph Dürr , Arturo Merino , José A. Soto , José Verschae

Consider a random graph model where each possible edge $e$ is present independently with some probability $p_e$. Given these probabilities, we want to build a large/heavy matching in the randomly generated graph. However, the only way we…

Data Structures and Algorithms · Computer Science 2010-09-01 Nikhil Bansal , Anupam Gupta , Jian Li , Julian Mestre , Viswanath Nagarajan , Atri Rudra

The exact matching problem is a constrained variant of the maximum matching problem: given a graph with each edge having a weight $0$ or $1$ and an integer $k$, the goal is to find a perfect matching of weight exactly $k$. Mulmuley,…

Data Structures and Algorithms · Computer Science 2024-05-07 Hitoshi Murakami , Yutaro Yamaguchi

We give an algorithm for finding the arboricity of a weighted, undirected graph, defined as the minimum number of spanning forests that cover all edges of the graph, in $\sqrt{n} m^{1+o(1)}$ time. This improves on the previous best bound of…

Data Structures and Algorithms · Computer Science 2025-07-22 Ruoxu Cen , Henry Fleischmann , George Z. Li , Jason Li , Debmalya Panigrahi

A maximum weighted matching for bipartite graphs $G=(A \cup B,E)$ can be found by using the algorithm of Edmonds and Karp with a Fibonacci Heap and a modified Dijkstra in $O(nm + n^2 \log{n})$ time where n is the number of nodes and m the…

Data Structures and Algorithms · Computer Science 2007-05-23 Daniel Etzold

In this paper, we consider the graph alignment problem, which is the problem of recovering, given two graphs, a one-to-one mapping between nodes that maximizes edge overlap. This problem can be viewed as a noisy version of the well-known…

Machine Learning · Statistics 2022-01-14 Georgina Hall , Laurent Massoulié

Random graph alignment refers to recovering the underlying vertex correspondence between two random graphs with correlated edges. This can be viewed as an average-case and noisy version of the well-known graph isomorphism problem. For the…

Machine Learning · Statistics 2021-08-18 Luca Ganassali , Laurent Massoulié , Marc Lelarge