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By prior work, there is a distributed algorithm that finds a maximal fractional matching (maximal edge packing) in $O(\Delta)$ rounds, where $\Delta$ is the maximum degree of the graph. We show that this is optimal: there is no distributed…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-12-24 Mika Göös , Juho Hirvonen , Jukka Suomela

This paper studies minimax optimization problems $\min_x \max_y f(x,y)$, where $f(x,y)$ is $m_x$-strongly convex with respect to $x$, $m_y$-strongly concave with respect to $y$ and $(L_x,L_{xy},L_y)$-smooth. Zhang et al. provided the…

Machine Learning · Computer Science 2020-10-20 Yuanhao Wang , Jian Li

The Maximal Independent Set (MIS) problem is one of the basics in the study of locality in distributed graph algorithms. This paper presents an extremely simple randomized algorithm providing a near-optimal local complexity for this…

Data Structures and Algorithms · Computer Science 2015-07-14 Mohsen Ghaffari

We present a $O(n^{\frac{3}{2}})$-time algorithm for the \emph{shortest (diagonal) flip path problem} for \emph{lattice} triangulations with $n$ points, improving over previous $O(n^2)$-time algorithms. For a large, natural class of inputs,…

Computational Geometry · Computer Science 2024-01-22 William Sims , Meera Sitharam

A $t$-ruling set of a graph $G = (V, E)$ is a vertex-subset $S \subseteq V$ that is independent and satisfies the property that every vertex $v \in V$ is at a distance of at most $t$ from some vertex in $S$. A \textit{maximal independent…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-07-16 Kishore Kothapalli , Sriram Pemmaraju

Cutwidth is a widely studied parameter that quantifies how well a graph can be decomposed along small edge-cuts. It complements pathwidth, which captures decomposition by small vertex separators, and it is well-known that cutwidth…

Data Structures and Algorithms · Computer Science 2025-02-25 Narek Bojikian , Vera Chekan , Stefan Kratsch

We study the problem of finding a maximal independent set (MIS) in the standard LOCAL model of distributed computing. Classical algorithms by Luby [JACM'86] and Alon, Babai, and Itai [JALG'86] find an MIS in $O(\log n)$ rounds in $n$-node…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-22 Seri Khoury , Aaron Schild

We study the complexity of fundamental distributed graph problems in the recently popular setting where information about the input graph is available to the nodes before the start of the computation. We focus on the most common such…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-03 Alkida Balliu , Thomas Boudier , Sebastian Brandt , Dennis Olivetti

Minimum-weight cut (min-cut) is a basic measure of a network's connectivity strength. While the min-cut can be computed efficiently in the sequential setting [Karger STOC'96], there was no efficient way for a distributed network to compute…

Data Structures and Algorithms · Computer Science 2020-11-17 Michal Dory , Yuval Efron , Sagnik Mukhopadhyay , Danupon Nanongkai

This paper presents a lower bound for optimizing a finite sum of $n$ functions, where each function is $L$-smooth and the sum is $\mu$-strongly convex. We show that no algorithm can reach an error $\epsilon$ in minimizing all functions from…

Machine Learning · Statistics 2015-10-06 Alekh Agarwal , Leon Bottou

The 2-opt heuristic is a very simple local search heuristic for the traveling salesperson problem. In practice it usually converges quickly to solutions within a few percentages of optimality. In contrast to this, its running-time is…

Data Structures and Algorithms · Computer Science 2023-08-02 Marvin Künnemann , Bodo Manthey , Rianne Veenstra

We discuss combinatorial algorithms for finding a maximum weight $f$-factor on an arbitrary multigraph, for given integral weights of magnitude at most $W$. For simple bipartite graphs the best-known time bound is $O(n^{2/3}\, m\, \log nW)$…

Data Structures and Algorithms · Computer Science 2020-10-05 Harold Gabow

We show sublinear-time algorithms for Max Cut and Max E2Lin$(q)$ on expanders in the adjacency list model that distinguishes instances with the optimal value more than $1-\varepsilon$ from those with the optimal value less than $1-\rho$ for…

Data Structures and Algorithms · Computer Science 2022-10-25 Pan Peng , Yuichi Yoshida

This paper studies the problem of stochastic bilevel optimization where the upper-level function is nonconvex with potentially unbounded smoothness and the lower-level function is strongly convex. This problem is motivated by meta-learning…

Machine Learning · Computer Science 2024-12-31 Xiaochuan Gong , Jie Hao , Mingrui Liu

We give an algorithm to find a mincut in an $n$-vertex, $m$-edge weighted directed graph using $\tilde O(\sqrt{n})$ calls to any maxflow subroutine. Using state of the art maxflow algorithms, this yields a directed mincut algorithm that…

Data Structures and Algorithms · Computer Science 2021-04-19 Ruoxu Cen , Jason Li , Danupon Nanongkai , Debmalya Panigrahi , Thatchaphol Saranurak

Currently, the best known tradeoff between approximation ratio and complexity for the Sparsest Cut problem is achieved by the algorithm in [Sherman, FOCS 2009]: it computes $O(\sqrt{(\log n)/\varepsilon})$-approximation using…

Data Structures and Algorithms · Computer Science 2025-07-11 Vladimir Kolmogorov

We give a 2-approximation algorithm for Non-Uniform Sparsest Cut that runs in time $n^{O(k)}$, where $k$ is the treewidth of the graph. This improves on the previous $2^{2^k}$-approximation in time $\poly(n) 2^{O(k)}$ due to Chlamt\'a\v{c}…

Data Structures and Algorithms · Computer Science 2013-05-08 Anupam Gupta , Kunal Talwar , David Witmer

We identify a sharp separation in the streaming space complexity of Maximum Cut when the algorithm must output an approximate cut (rather than only the approximate value). For dense graphs, we show that $O(n/\varepsilon^2)$ space is…

Data Structures and Algorithms · Computer Science 2026-05-12 Yang P. Liu , Hoai-An Nguyen , Noah G. Singer , David P. Woodruff

Optimization problems consist of either maximizing or minimizing an objective function. Instead of looking for a maximum solution (resp. minimum solution), one can find a minimum maximal solution (resp. maximum minimal solution). Such…

Data Structures and Algorithms · Computer Science 2018-11-08 Kaveh Khoshkhah , Mehdi Khosravian Ghadikolaei , Jerome Monnot , Florian Sikora

This paper ties the line of work on algorithms that find an O(sqrt(log(n)))-approximation to the sparsest cut together with the line of work on algorithms that run in sub-quadratic time by using only single-commodity flows. We present an…

Data Structures and Algorithms · Computer Science 2009-08-11 Jonah Sherman
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