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Related papers: Streaming Lower Bounds for Approximating MAX-CUT

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When rows of an $n \times d$ matrix $A$ are given in a stream, we study algorithms for approximating the top eigenvector of the matrix ${A}^TA$ (equivalently, the top right singular vector of $A$). We consider worst case inputs $A$ but…

Data Structures and Algorithms · Computer Science 2024-12-17 Praneeth Kacham , David P. Woodruff

Considerable effort has been devoted to the development of streaming algorithms for analyzing massive graphs. Unfortunately, many results have been negative, establishing that a wide variety of problems require $\Omega(n^2)$ space to solve.…

Data Structures and Algorithms · Computer Science 2015-08-11 Justin Thaler

We give O(log^2 n)-approximation algorithm based on the cut-matching framework of [10, 13, 14] for computing the sparsest cut on directed graphs. Our algorithm uses only O(log^2 n) single commodity max-flow computations and thus breaks the…

Data Structures and Algorithms · Computer Science 2015-03-17 Anand Louis

Computing the approximate quantiles or ranks of a stream is a fundamental task in data monitoring. Given a stream of elements $x_1, x_2, \dots, x_n$ and a query $x$, a relative-error quantile estimation algorithm can estimate the rank of…

Data Structures and Algorithms · Computer Science 2024-11-05 Elena Gribelyuk , Pachara Sawettamalya , Hongxun Wu , Huacheng Yu

Storing a counter incremented $N$ times would naively consume $O(\log N)$ bits of memory. In 1978 Morris described the very first streaming algorithm: the "Morris Counter". His algorithm's space bound is a random variable, and it has been…

Data Structures and Algorithms · Computer Science 2022-04-01 Jelani Nelson , Huacheng Yu

In this paper, we develop the first one-pass streaming algorithm for submodular maximization that does not evaluate the entire stream even once. By carefully subsampling each element of data stream, our algorithm enjoys the tightest…

Machine Learning · Computer Science 2018-02-21 Moran Feldman , Amin Karbasi , Ehsan Kazemi

In this paper, we consider two fundamental cut approximation problems on large graphs. We prove new lower bounds for both problems that are optimal up to logarithmic factors. The first problem is to approximate cuts in balanced directed…

Data Structures and Algorithms · Computer Science 2024-06-21 Yu Cheng , Max Li , Honghao Lin , Zi-Yi Tai , David P. Woodruff , Jason Zhang

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

The edit distance is a way of quantifying how similar two strings are to one another by counting the minimum number of character insertions, deletions, and substitutions required to transform one string into the other. In this paper we…

Data Structures and Algorithms · Computer Science 2016-07-14 Diptarka Chakraborty , Elazar Goldenberg , Michal Koucký

We study the problem of solving linear program in the streaming model. Given a constraint matrix $A\in \mathbb{R}^{m\times n}$ and vectors $b\in \mathbb{R}^m, c\in \mathbb{R}^n$, we develop a space-efficient interior point method that…

Data Structures and Algorithms · Computer Science 2023-05-19 S. Cliff Liu , Zhao Song , Hengjie Zhang , Lichen Zhang , Tianyi Zhou

We initiate the investigation of the parameterized complexity of Diameter and Connectivity in the streaming paradigm. On the positive end, we show that knowing a vertex cover of size $k$ allows for algorithms in the Adjacency List (AL)…

Data Structures and Algorithms · Computer Science 2024-07-19 Jelle J. Oostveen , Erik Jan van Leeuwen

We study polynomial-time approximation algorithms for (edge/vertex) Sparsest Cut and Small Set Expansion in terms of $k$, the number of edges or vertices cut in the optimal solution. Our main results are $\mathcal{O}(\text{polylog}\,…

Data Structures and Algorithms · Computer Science 2024-03-15 Aditya Anand , Euiwoong Lee , Jason Li , Thatchaphol Saranurak

The problem of (approximately) counting the number of triangles in a graph is one of the basic problems in graph theory. In this paper we study the problem in the streaming model. We study the amount of memory required by a randomized…

Data Structures and Algorithms · Computer Science 2013-04-05 Vladimir Braverman , Rafail Ostrovsky , Dan Vilenchik

We consider the problem of monotone, submodular maximization over a ground set of size $n$ subject to cardinality constraint $k$. For this problem, we introduce the first deterministic algorithms with linear time complexity; these…

Data Structures and Algorithms · Computer Science 2021-03-09 Alan Kuhnle

This paper studies the set cover problem under the semi-streaming model. The underlying set system is formalized in terms of a hypergraph $G = (V, E)$ whose edges arrive one-by-one and the goal is to construct an edge cover $F \subseteq E$…

Data Structures and Algorithms · Computer Science 2014-05-09 Yuval Emek , Adi Rosen

We consider the max-cut and max-$k$-cut problems under graph-based constraints. Our approach can handle any constraint specified using monadic second-order (MSO) logic on graphs of constant treewidth. We give a $\frac{1}{2}$-approximation…

Computational Complexity · Computer Science 2018-10-19 Martin Koutecký , Jon Lee , Viswanath Nagarajan , Xiangkun Shen

Traditional graph-based semi-supervised learning (SSL) approaches, even though widely applied, are not suited for massive data and large label scenarios since they scale linearly with the number of edges $|E|$ and distinct labels $m$. To…

Machine Learning · Computer Science 2016-05-17 Sujith Ravi , Qiming Diao

A fundamental question in streaming complexity is whether every space-efficient turnstile algorithm is implicitly a linear sketch. The landmark work of Li, Nguyen, and Woodruff [LNW14] established an equivalence between the two, but their…

Data Structures and Algorithms · Computer Science 2026-04-27 Cheng Jiang , Yinchen Liu , Huacheng Yu

We improve on random sampling techniques for approximately solving problems that involve cuts and flows in graphs. We give a near-linear-time construction that transforms any graph on n vertices into an O(n\log n)-edge graph on the same…

Data Structures and Algorithms · Computer Science 2007-05-23 Andras Benczur , David R. Karger

We study graph computations in an enhanced data streaming setting, where a space-bounded client reading the edge stream of a massive graph may delegate some of its work to a cloud service. We seek algorithms that allow the client to verify…

Data Structures and Algorithms · Computer Science 2020-07-08 Amit Chakrabarti , Prantar Ghosh , Justin Thaler