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Let $A$ be an $n\times n$ random matrix whose entries are i.i.d. with mean $0$ and variance $1$. We present a deterministic polynomial time algorithm which, with probability at least $1-2\exp(-\Omega(\epsilon n))$ in the choice of $A$,…

Probability · Mathematics 2020-12-02 Vishesh Jain , Ashwin Sah , Mehtaab Sawhney

We develop faster approximation algorithms for Metric-TSP building on recent, nearly linear time approximation schemes for the LP relaxation [Chekuri and Quanrud, 2017]. We show that the LP solution can be sparsified via cut-sparsification…

Data Structures and Algorithms · Computer Science 2018-02-06 Chandra Chekuri , Kent Quanrud

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

In graph sparsification, the goal has almost always been of {global} nature: compress a graph into a smaller subgraph ({sparsifier}) that maintains certain features of the original graph. Algorithms can then run on the sparsifier, which in…

Data Structures and Algorithms · Computer Science 2021-05-06 Shay Solomon

We give a fully dynamic deterministic algorithm for maintaining a maximal matching of an $n$-vertex graph in $\tilde{O}(n^{8/9})$ amortized update time. This breaks the long-standing $\Omega(n)$-update-time barrier on dense graphs,…

Data Structures and Algorithms · Computer Science 2025-09-01 Aaron Bernstein , Sayan Bhattacharya , Peter Kiss , Thatchaphol Saranurak

Let $\mathbf S \in \mathbb R^{n \times n}$ satisfy $\|\mathbf 1-\mathbf S\|_2\le\epsilon n$, where $\mathbf 1$ is the all ones matrix and $\|\cdot\|_2$ is the spectral norm. It is well-known that there exists such an $\mathbf S$ with just…

Data Structures and Algorithms · Computer Science 2024-01-15 Rajarshi Bhattacharjee , Gregory Dexter , Cameron Musco , Archan Ray , Sushant Sachdeva , David P Woodruff

We present improved algorithms for short cycle decomposition of a graph. Short cycle decompositions were introduced in the recent work of Chu et al, and were used to make progress on several questions in graph sparsification. For all…

Data Structures and Algorithms · Computer Science 2019-01-15 Yang P. Liu , Sushant Sachdeva , Zejun Yu

We study the maximum weight perfect $f$-factor problem on any general simple graph $G=(V,E,w)$ with positive integral edge weights $w$, and $n=|V|$, $m=|E|$. When we have a function $f:V\rightarrow \mathbb{N}_+$ on vertices, a perfect…

Data Structures and Algorithms · Computer Science 2020-03-18 Ran Duan , Haoqing He , Tianyi Zhang

Maximum weight matching is one of the most fundamental combinatorial optimization problems with a wide range of applications in data mining and bioinformatics. Developing distributed weighted matching algorithms is challenging due to the…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-06 Sepehr Assadi , MohammadHossein Bateni , Vahab Mirrokni

We propose polynomial-time algorithms that sparsify planar and bounded-genus graphs while preserving optimal or near-optimal solutions to Steiner problems. Our main contribution is a polynomial-time algorithm that, given an unweighted graph…

Data Structures and Algorithms · Computer Science 2017-07-12 Marcin Pilipczuk , Michał Pilipczuk , Piotr Sankowski , Erik Jan van Leeuwen

Let $\mathcal{C}$ and $\mathcal{D}$ be hereditary graph classes. Consider the following problem: given a graph $G\in\mathcal{D}$, find a largest, in terms of the number of vertices, induced subgraph of $G$ that belongs to $\mathcal{C}$. We…

Computational Complexity · Computer Science 2019-10-03 Jana Novotná , Karolina Okrasa , Michał Pilipczuk , Paweł Rzążewski , Erik Jan van Leeuwen , Bartosz Walczak

Stochastic optimization algorithms update models with cheap per-iteration costs sequentially, which makes them amenable for large-scale data analysis. Such algorithms have been widely studied for structured sparse models where the sparsity…

Machine Learning · Computer Science 2019-05-10 Baojian Zhou , Feng Chen , Yiming Ying

The problem of optimal precision switching for the conjugate gradient (CG) method applied to sparse linear systems is considered. A sparse matrix is defined as an $n\!\times\!n$ matrix with $m\!=\!O(n)$ nonzero entries. The algorithm first…

Numerical Analysis · Mathematics 2026-03-03 Alexander V. Prolubnikov

Cut and spectral sparsification of graphs have numerous applications, including e.g. speeding up algorithms for cuts and Laplacian solvers. These powerful notions have recently been extended to hypergraphs, which are much richer and may…

Data Structures and Algorithms · Computer Science 2021-04-13 Michael Kapralov , Robert Krauthgamer , Jakab Tardos , Yuichi Yoshida

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

We develop a new algorithmic technique that allows to transfer some constant time approximation algorithms for general graphs into random order streaming algorithms. We illustrate our technique by proving that in random order streams with…

Data Structures and Algorithms · Computer Science 2017-11-15 Pan Peng , Christian Sohler

We consider the sensitivity of algorithms for the maximum matching problem against edge and vertex modifications. Algorithms with low sensitivity are desirable because they are robust to edge failure or attack. In this work, we show a…

Data Structures and Algorithms · Computer Science 2020-09-11 Yuichi Yoshida , Samson Zhou

Given a simple weighted directed graph $G = (V, E, \omega)$ on $n$ vertices as well as two designated terminals $s, t\in V$, our goal is to compute the shortest path from $s$ to $t$ avoiding any pair of presumably failed edges $f_1, f_2\in…

Data Structures and Algorithms · Computer Science 2024-04-23 Shiri Chechik , Tianyi Zhang

We present two on-line algorithms for maintaining a topological order of a directed $n$-vertex acyclic graph as arcs are added, and detecting a cycle when one is created. Our first algorithm handles $m$ arc additions in $O(m^{3/2})$ time.…

Data Structures and Algorithms · Computer Science 2011-05-13 Bernhard Haeupler , Telikepalli Kavitha , Rogers Mathew , Siddhartha Sen , Robert Endre Tarjan

We present new approaches to constructing graph sparsifiers --- weighted subgraphs for which every cut has the same value as the original graph, up to a factor of $(1 \pm \epsilon)$. Our first approach independently samples each edge $uv$…

Data Structures and Algorithms · Computer Science 2010-08-10 Wai Shing Fung , Nicholas J. A. Harvey