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We consider the minimum cut problem in undirected, weighted graphs. We give a simple algorithm to find a minimum cut that $2$-respects (cuts two edges of) a spanning tree $T$ of a graph $G$. This procedure can be used in place of the…

Data Structures and Algorithms · Computer Science 2020-06-11 Nalin Bhardwaj , Antonio Molina Lovett , Bryce Sandlund

We present an $\tilde O(m+n^{1.5})$-time randomized algorithm for maximum cardinality bipartite matching and related problems (e.g. transshipment, negative-weight shortest paths, and optimal transport) on $m$-edge, $n$-node graphs. For…

Data Structures and Algorithms · Computer Science 2021-10-15 Jan van den Brand , Yin-Tat Lee , Danupon Nanongkai , Richard Peng , Thatchaphol Saranurak , Aaron Sidford , Zhao Song , Di Wang

In this paper we provide a parallel algorithm that given any $n$-node $m$-edge directed graph and source vertex $s$ computes all vertices reachable from $s$ with $\tilde{O}(m)$ work and $n^{1/2 + o(1)}$ depth with high probability in $n$ .…

Data Structures and Algorithms · Computer Science 2019-12-09 Arun Jambulapati , Yang P. Liu , Aaron Sidford

Vertex deletion problems ask whether it is possible to delete at most $k$ vertices from a graph so that the resulting graph belongs to a specified graph class. Over the past years, the parameterized complexity of vertex deletion to a…

Data Structures and Algorithms · Computer Science 2017-08-07 Eduard Eiben , Robert Ganian , O-joung Kwon

We give a deterministic $m^{1+o(1)}$ time algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with $m$ edges and polynomially bounded integral demands, costs, and capacities. As a consequence, we obtain the…

Data Structures and Algorithms · Computer Science 2023-09-29 Jan van den Brand , Li Chen , Rasmus Kyng , Yang P. Liu , Richard Peng , Maximilian Probst Gutenberg , Sushant Sachdeva , Aaron Sidford

Sensitive datasets are often underutilized in research and industry due to privacy concerns, limiting the potential of valuable data-driven insights. Synthetic data generation presents a promising solution to address this challenge by…

Computation · Statistics 2026-01-27 Ali Furkan Kalay

In this paper, we develop new tools and connections for exponential time approximation. In this setting, we are given a problem instance and a parameter $\alpha>1$, and the goal is to design an $\alpha$-approximation algorithm with the…

Data Structures and Algorithms · Computer Science 2017-08-14 Nikhil Bansal , Parinya Chalermsook , Bundit Laekhanukit , Danupon Nanongkai , Jesper Nederlof

In this paper we demonstrate that, ignoring computational constraints, it is possible to privately release synthetic databases that are useful for large classes of queries -- much larger in size than the database itself. Specifically, we…

Data Structures and Algorithms · Computer Science 2011-09-13 Avrim Blum , Katrina Ligett , Aaron Roth

Recently there has been increasing interest in developing and deploying deep graph learning algorithms for many tasks, such as fraud detection and recommender systems. Albeit, there is a limited number of publicly available graph-structured…

Machine Learning · Computer Science 2023-10-06 Sajad Darabi , Piotr Bigaj , Dawid Majchrowski , Artur Kasymov , Pawel Morkisz , Alex Fit-Florea

A graph $G$ is said to be a $(k,\ell)$-graph if its vertex set can be partitioned into $k$ independent sets and $\ell$ cliques. It is well established that the recognition problem for $(k,\ell)$-graphs is NP-complete whenever $k \geq 3$ or…

Discrete Mathematics · Computer Science 2025-10-21 Flavia Bonomo-Braberman , Min Chih Lin , Ignacio Maqueda

Effective Resistance (ER) is a fundamental tool in various graph learning tasks. In this paper, we address the problem of efficiently approximating ER on a graph $\mathcal{G}=(\mathcal{V},\mathcal{E})$ with $n$ vertices and $m$ edges.…

Data Structures and Algorithms · Computer Science 2025-07-08 Yichun Yang , Rong-Hua Li , Meihao Liao , Guoren Wang

In this paper, we revisit the classic approximate All-Pairs Shortest Paths (APSP) problem in undirected graphs. For unweighted graphs, we provide an algorithm for $2$-approximate APSP in $\tilde O(n^{2.5-r}+n^{\omega(r)})$ time, for any…

Data Structures and Algorithms · Computer Science 2023-10-31 Michal Dory , Sebastian Forster , Yael Kirkpatrick , Yasamin Nazari , Virginia Vassilevska Williams , Tijn de Vos

In numerical linear algebra, considerable effort has been devoted to obtaining faster algorithms for linear systems whose underlying matrices exhibit structural properties. A prominent success story is the method of generalized nested…

Data Structures and Algorithms · Computer Science 2023-10-26 Sally Dong , Gramoz Goranci , Lawrence Li , Sushant Sachdeva , Guanghao Ye

One of the simplest problems on directed graphs is that of identifying the set of vertices reachable from a designated source vertex. This problem can be solved easily sequentially by performing a graph search, but efficient parallel…

Data Structures and Algorithms · Computer Science 2017-11-07 Jeremy T. Fineman

Among the most important graph parameters is the Diameter, the largest distance between any two vertices. There are no known very efficient algorithms for computing the Diameter exactly. Thus, much research has been devoted to how fast this…

Data Structures and Algorithms · Computer Science 2021-03-31 Arturs Backurs , Liam Roditty , Gilad Segal , Virginia Vassilevska Williams , Nicole Wein

For a graph $G$ on $n$ vertices, naively sampling the position of a random walk of at time $t$ requires work $\Omega(t)$. We desire local access algorithms supporting $\text{position}(G,s,t)$ queries, which return the position of a random…

Data Structures and Algorithms · Computer Science 2021-02-16 Amartya Shankha Biswas , Edward Pyne , Ronitt Rubinfeld

In the decremental single-source shortest paths (SSSP) problem we want to maintain the distances between a given source node $s$ and every other node in an $n$-node $m$-edge graph $G$ undergoing edge deletions. While its static counterpart…

Data Structures and Algorithms · Computer Science 2018-08-20 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

The family of $(k,\ell)$-sparse graphs, introduced by Lorea, plays a central role in combinatorial optimization and has a wide range of applications, particularly in rigidity theory. A key algorithmic problem is to decide whether a given…

Data Structures and Algorithms · Computer Science 2026-04-15 Bence Deák , Péter Madarasi

A $(1 \pm \epsilon)$-sparsifier of a hypergraph $G(V,E)$ is a (weighted) subgraph that preserves the value of every cut to within a $(1 \pm \epsilon)$-factor. It is known that every hypergraph with $n$ vertices admits a $(1 \pm…

Data Structures and Algorithms · Computer Science 2024-07-08 Sanjeev Khanna , Aaron L. Putterman , Madhu Sudan

We give an algorithm to find a minimum cut in an edge-weighted directed graph with $n$ vertices and $m$ edges in $\tilde O(n\cdot \max(m^{2/3}, n))$ time. This improves on the 30 year old bound of $\tilde O(nm)$ obtained by Hao and Orlin…

Data Structures and Algorithms · Computer Science 2021-11-18 Ruoxu Cen , Jason Li , Danupon Nanongkai , Debmalya Panigrahi , Kent Quanrud , Thatchaphol Saranurak