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The edit distance between two graphs on the same vertex set is defined to be size of the symmetric difference of their edge sets. The edit distance function of a hereditary property, $\mathcal{H}$, is a function of $p$ and measures,…

Combinatorics · Mathematics 2011-02-22 Ryan Martin , Tracy McKay

A family of graphs $\mathcal{F}$ is $H$-intersecting if the edge intersection of any two graphs in $\mathcal{F}$ contains a copy of a fixed graph $H$. A fundamental problem is to determine the maximum size of such a family. The trivial…

Combinatorics · Mathematics 2025-11-25 Paul Hamrick , Gary Hu

In discrepancy minimization problems, we are given a family of sets $\mathcal{S} = \{S_1,\dots,S_m\}$, with each $S_i \in \mathcal{S}$ a subset of some universe $U = \{u_1,\dots,u_n\}$ of $n$ elements. The goal is to find a coloring $\chi :…

Data Structures and Algorithms · Computer Science 2018-12-14 Kasper Green Larsen

For a graph $G$ and a hereditary property $\mathcal{P}$, let $\text{ex}(G,\mathcal{P})$ denote the maximum number of edges of a subgraph of $G$ that belongs to $\mathcal{P}$. We prove that for every non-trivial hereditary property…

Combinatorics · Mathematics 2024-05-16 Alexander Clifton , Hong Liu , Letícia Mattos , Michael Zheng

Counting small patterns in a large dataset is a fundamental algorithmic task. The most common version of this task is subgraph/homomorphism counting, wherein we count the number of occurrences of a small pattern graph $H$ in an input graph…

Data Structures and Algorithms · Computer Science 2025-10-21 Daniel Paul-Pena , C. Seshadhri

Given a weighted undirected graph $G=(V,E,w)$, a hopset $H$ of hopbound $\beta$ and stretch $(1+\epsilon)$ is a set of edges such that for any pair of nodes $u, v \in V$, there is a path in $G \cup H$ of at most $\beta$ hops, whose length…

Data Structures and Algorithms · Computer Science 2022-08-05 Jakub Łącki , Yasamin Nazari

We study fundamental graph parameters such as the Diameter and Radius in directed graphs, when distances are measured using a somewhat unorthodox but natural measure: the distance between $u$ and $v$ is the minimum of the shortest path…

Data Structures and Algorithms · Computer Science 2019-06-18 Mina Dalirrooyfard , Virginia Vassilevska Williams , Nikhil Vyas , Nicole Wein , Yinzhan Xu , Yuancheng Yu

In the restricted shortest paths problem, we are given a graph $G$ whose edges are assigned two non-negative weights: lengths and delays, a source $s$, and a delay threshold $D$. The goal is to find, for each target $t$, the length of the…

Data Structures and Algorithms · Computer Science 2024-10-23 Vikrant Ashvinkumar , Aaron Bernstein , Adam Karczmarz

The Spanning Tree Congestion (STC) problem is the following NP-hard problem: given a graph $G$, construct a spanning tree $T$ of $G$ minimizing its maximum edge congestion where the congestion of an edge $e\in T$ is the number of edges $uv$…

Data Structures and Algorithms · Computer Science 2026-05-05 Petr Kolman

A homomorphism from a graph $G$ to a graph $H$ is an edge-preserving mapping from $V(G)$ to $V(H)$. In the graph homomorphism problem, denoted by $Hom(H)$, the graph $H$ is fixed and we need to determine if there exists a homomorphism from…

Discrete Mathematics · Computer Science 2023-12-08 Carla Groenland , Isja Mannens , Jesper Nederlof , Marta Piecyk , Paweł Rzążewski

We initiate the study of diameter computation in geometric intersection graphs from the fine-grained complexity perspective. A geometric intersection graph is a graph whose vertices correspond to some shapes in $d$-dimensional Euclidean…

Computational Geometry · Computer Science 2022-03-11 Karl Bringmann , Sándor Kisfaludi-Bak , Marvin Künnemann , André Nusser , Zahra Parsaeian

A hereditary property of graphs is a collection of graphs which is closed under taking induced subgraphs. The speed of \P is the function n \mapsto |\P_n|, where \P_n denotes the graphs of order n in \P. It was shown by Alekseev, and by…

Combinatorics · Mathematics 2009-05-13 Noga Alon , Jozsef Balogh , Bela Bollobas , Robert Morris

We study sublinear time algorithms for estimating the size of maximum matching. After a long line of research, the problem was finally settled by Behnezhad [FOCS'22], in the regime where one is willing to pay an approximation factor of $2$.…

Data Structures and Algorithms · Computer Science 2023-04-28 Sayan Bhattacharya , Peter Kiss , Thatchaphol Saranurak

For two independent Erd\H{o}s-R\'enyi graphs $\mathbf G(n,p)$, we study the maximal overlap (i.e., the number of common edges) of these two graphs over all possible vertex correspondence. We present a polynomial-time algorithm which finds a…

Probability · Mathematics 2022-10-17 Jian Ding , Hang Du , Shuyang Gong

The partial coloring method is one of the most powerful and widely used method in combinatorial discrepancy problems. However, in many cases it leads to sub-optimal bounds as the partial coloring step must be iterated a logarithmic number…

Data Structures and Algorithms · Computer Science 2017-07-13 Nikhil Bansal , Shashwat Garg

Some of the most fundamental and well-studied graph parameters are the Diameter (the largest shortest paths distance) and Radius (the smallest distance for which a "center" node can reach all other nodes). The natural and important…

Data Structures and Algorithms · Computer Science 2019-04-29 Mina Dalirrooyfard , Virginia Vassilevska Williams , Nikhil Vyas , Nicole Wein

We prove that any extended formulation that approximates the matching polytope on $n$-vertex graphs up to a factor of $(1+\varepsilon)$ for any $\frac2n \le \varepsilon \le 1$ must have at least $\binom{n}{{\alpha}/{\varepsilon}}$ defining…

Computational Complexity · Computer Science 2017-11-29 Makrand Sinha

Recent works of Alon-Shapira and R\"odl-Schacht have demonstrated that every hereditary property of undirected graphs or hypergraphs is testable with one-sided error; informally, this means that if a graph or hypergraph satisfies that…

Combinatorics · Mathematics 2009-05-12 Tim Austin , Terence Tao

Although the Laplace approximation offers a simple route to uncertainty quantification in deep neural networks, its reliance on inverting large Hessian matrices has motivated a range of computationally feasible low-dimensional or sparse…

Machine Learning · Statistics 2026-05-12 Swarnali Raha , Kshitij Khare , Rohit K Patra

In the Densest k-Subgraph problem, given a graph G and a parameter k, one needs to find a subgraph of G induced on k vertices that contains the largest number of edges. There is a significant gap between the best known upper and lower…

Data Structures and Algorithms · Computer Science 2010-01-19 Aditya Bhaskara , Moses Charikar , Eden Chlamtac , Uriel Feige , Aravindan Vijayaraghavan