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Recent years have seen extensive research on directed graph sparsification. In this work, we initiate the study of fast fully dynamic spectral and cut sparsification algorithms for directed graphs. We introduce a new notion of spectral…

Data Structures and Algorithms · Computer Science 2025-07-29 Yibin Zhao

The Graph Isomorphism problem has both theoretical and practical interest. In this paper we present an algorithm, called conauto-1.2, that efficiently tests whether two graphs are isomorphic, and finds an isomorphism if they are. This…

Data Structures and Algorithms · Computer Science 2011-06-23 Jose Luis Lopez-Presa , Antonio Fernandez Anta

Notions of graph similarity provide alternative perspective on the graph isomorphism problem and vice-versa. In this paper, we consider measures of similarity arising from mismatch norms as studied in Gervens and Grohe: the edit distance…

Discrete Mathematics · Computer Science 2026-05-07 He Sun , Danny Vagnozzi

We first show that the Traveling Salesman Problem in an n-vertex graph with average degree bounded by d can be solved in O*(2^{(1-\eps_d)n}) time and exponential space for a constant \eps_d depending only on d, where the O*-notation…

Data Structures and Algorithms · Computer Science 2013-02-18 Marek Cygan , Marcin Pilipczuk

Finding coarse representations of large graphs is an important computational problem in the fields of scientific computing, large scale graph partitioning, and the reduction of geometric meshes. Of particular interest in all of these fields…

Discrete Mathematics · Computer Science 2022-04-26 Christopher Brissette , Andy Huang , George Slota

The problem of sparsifying a graph or a hypergraph while approximately preserving its cut structure has been extensively studied and has many applications. In a seminal work, Bencz\'ur and Karger (1996) showed that given any $n$-vertex…

Data Structures and Algorithms · Computer Science 2021-06-22 Yu Chen , Sanjeev Khanna , Ansh Nagda

In a seminal paper on finding large matchings in sparse random graphs, Karp and Sipser proposed two algorithms for this task. The second algorithm has been intensely studied, but due to technical difficulties, the first algorithm has…

Combinatorics · Mathematics 2018-11-14 Michael Anastos , Alan Frieze

We present a new sublinear time algorithm for approximating the spectral density (eigenvalue distribution) of an $n\times n$ normalized graph adjacency or Laplacian matrix. The algorithm recovers the spectrum up to $\epsilon$ accuracy in…

Data Structures and Algorithms · Computer Science 2022-04-18 Vladimir Braverman , Aditya Krishnan , Christopher Musco

For a class $\mathcal{G}$ of graphs, the objective of \textsc{Subgraph Complementation to} $\mathcal{G}$ is to find whether there exists a subset $S$ of vertices of the input graph $G$ such that modifying $G$ by complementing the subgraph…

Data Structures and Algorithms · Computer Science 2023-03-29 Dhanyamol Antony , Sagartanu Pal , R. B. Sandeep

In this paper, we show that given a weighted, directed planar graph $G$, and any $\epsilon >0$, there exists a polynomial time and $O(n^{\frac{1}{2}+\epsilon})$ space algorithm that computes the shortest path between two fixed vertices in…

Computational Complexity · Computer Science 2015-02-10 Diptarka Chakraborty , Raghunath Tewari

Given a signed permutation on $n$ elements, we need to sort it with the fewest reversals. This is a fundamental algorithmic problem motivated by applications in comparative genomics, as it allows to accurately model rearrangements in small…

Data Structures and Algorithms · Computer Science 2023-08-31 Bartłomiej Dudek , Paweł Gawrychowski , Tatiana Starikovskaya

We present an algorithm for maintaining maximal matching in a graph under addition and deletion of edges. Our data structure is randomized that takes O(log n) expected amortized time for each edge update where n is the number of vertices in…

Data Structures and Algorithms · Computer Science 2016-08-03 Surender Baswana , Manoj Gupta , Sandeep Sen

Given a graph $G=(V, E)$ and and a proper labeling $f$ from $V$ to $\{1, ..., n\}$, we define $B(f)$ as the maximum absolute difference between $f(u)$ and $f(v)$ where $(u,v)\in E$. The bandwidth of $G$ is the minimum $B(f)$ for all $f$.…

Data Structures and Algorithms · Computer Science 2012-11-02 Hao-Hsiang Hung

Core decomposition is a classic technique for discovering densely connected regions in a graph with large range of applications. Formally, a $k$-core is a maximal subgraph where each vertex has at least $k$ neighbors. A natural extension of…

Data Structures and Algorithms · Computer Science 2023-01-31 Nikolaj Tatti

We initiate a systematic study of algorithms that are both differentially private and run in sublinear time for several problems in which the goal is to estimate natural graph parameters. Our main result is a differentially-private…

Data Structures and Algorithms · Computer Science 2022-03-15 Jeremiah Blocki , Elena Grigorescu , Tamalika Mukherjee

For two unlabeled graphs $G_1,G_2$ independently sub-sampled from an Erd\H{o}s-R\'enyi graph $\mathbf G(n,p)$ by keeping each edge with probability $s$, we aim to recover \emph{as many as possible} of the corresponding vertex pairs. We…

Probability · Mathematics 2025-02-18 Hang Du

The Euler genus of a graph is a fundamental and well-studied parameter in graph theory and topology. Computing it has been shown to be NP-hard by [Thomassen '89 & '93], and it is known to be fixed-parameter tractable. However, the…

Data Structures and Algorithms · Computer Science 2013-11-04 Chandra Chekuri , Anastasios Sidiropoulos

In the past decades for more and more graph classes the Graph Isomorphism Problem was shown to be solvable in polynomial time. An interesting family of graph classes arises from intersection graphs of geometric objects. In this work we show…

Data Structures and Algorithms · Computer Science 2016-06-23 Daniel Neuen

In Gaussian graphical model selection, noise-corrupted samples present significant challenges. It is known that even minimal amounts of noise can obscure the underlying structure, leading to fundamental identifiability issues. A recent line…

Machine Learning · Statistics 2024-05-09 Abrar Zahin , Rajasekhar Anguluri , Lalitha Sankar , Oliver Kosut , Gautam Dasarathy

We consider the problem of partitioning a graph into a non-fixed number of non-overlapping subgraphs of maximum density. The density of a partition is the sum of the densities of the subgraphs, where the density of a subgraph is its average…

Computational Complexity · Computer Science 2022-02-17 Cristina Bazgan , Katrin Casel , Pierre Cazals