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Let $H_n$ be a graph on $n$ vertices and let $\ber{H_n}$ denote the complement of $H_n$. Suppose that $\Delta = \Delta(n)$ is the maximum degree of $\ber{H_n}$. We analyse three algorithms for sampling $d$-regular subgraphs ($d$-factors) of…

Combinatorics · Mathematics 2019-10-25 Pu Gao , Catherine Greenhill

We study streaming algorithms for Correlation Clustering. Given a graph as an arbitrary-order stream of edges, with each edge labeled as positive or negative, the goal is to partition the vertices into disjoint clusters, such that the…

Data Structures and Algorithms · Computer Science 2025-10-14 Yinhao Dong , Shan Jiang , Shi Li , Pan Peng

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

In this paper, we consider the problem of approximating the densest subgraph in the dynamic graph stream model. In this model of computation, the input graph is defined by an arbitrary sequence of edge insertions and deletions and the goal…

Data Structures and Algorithms · Computer Science 2015-06-16 Andrew McGregor , David Tench , Sofya Vorotnikova , Hoa T. Vu

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 prove that any semi-streaming algorithm for $(1-\epsilon)$-approximation of maximum bipartite matching requires \[ \Omega(\frac{\log{(1/\epsilon)}}{{\log{(1/\beta)}}}) \] passes, where $\beta \in (0,1)$ is the largest parameter so that…

Data Structures and Algorithms · Computer Science 2023-10-12 Sepehr Assadi , Janani Sundaresan

A semi-streaming algorithm in dynamic graph streams processes any $n$-vertex graph by making one or multiple passes over a stream of insertions and deletions to edges of the graph and using $O(n \cdot \mbox{polylog}(n))$ space.…

Data Structures and Algorithms · Computer Science 2024-07-31 Sepehr Assadi , Soheil Behnezhad , Christian Konrad , Kheeran K. Naidu , Janani Sundaresan

We provide new high-accuracy randomized algorithms for solving linear systems and regression problems that are well-conditioned except for $k$ large singular values. For solving such $d \times d$ positive definite system our algorithms…

Data Structures and Algorithms · Computer Science 2025-07-17 Michał Dereziński , Aaron Sidford

Randomized parallel algorithms for many fundamental problems achieve optimal linear work in expectation, but upgrading this guarantee to hold with high probability (whp) remains a recurring theoretical challenge. In this paper, we address…

Data Structures and Algorithms · Computer Science 2026-03-03 Chase Hutton , Adam Melrod

A \emph{saddlepoint} of an $n \times n$ matrix is an entry that is the maximum of its row and the minimum of its column. Saddlepoints give the \emph{value} of a two-player zero-sum game, corresponding to its pure-strategy Nash equilibria;…

Computational Complexity · Computer Science 2024-01-17 Justin Dallant , Frederik Haagensen , Riko Jacob , László Kozma , Sebastian Wild

We present algorithms for the Max-Cover and Max-Unique-Cover problems in the data stream model. The input to both problems are $m$ subsets of a universe of size $n$ and a value $k\in [m]$. In Max-Cover, the problem is to find a collection…

Data Structures and Algorithms · Computer Science 2021-02-18 Andrew McGregor , David Tench , Hoa T. Vu

The area of sublinear algorithms have recently received a lot of attention. In this setting, one has to choose specific access model for the input, as the algorithm does not have time to pre-process or even to see the whole input. A…

Data Structures and Algorithms · Computer Science 2020-09-24 Jakub Tětek

A single-commodity congestion approximator for a graph is a compact data structure that approximately predicts the edge congestion required to route any set of single-commodity flow demands in a network. A hierarchical congestion…

Data Structures and Algorithms · Computer Science 2025-12-22 Monika Henzinger , Robin Münk , Harald Räcke

This paper resolves one of the longest standing basic problems in the streaming computational model. Namely, optimal construction of quantile sketches. An $\varepsilon$ approximate quantile sketch receives a stream of items $x_1,\ldots,x_n$…

Data Structures and Algorithms · Computer Science 2016-04-07 Zohar Karnin , Kevin Lang , Edo Liberty

We prove a lower bound on the space complexity of two-pass semi-streaming algorithms that approximate the maximum matching problem. The lower bound is parameterized by the density of Ruzsa-Szemeredi graphs: * Any two-pass semi-streaming…

Data Structures and Algorithms · Computer Science 2021-08-17 Sepehr Assadi

We consider the independent set problem in the semi-streaming model. For any input graph $G=(V, E)$ with $n$ vertices, an independent set is a set of vertices with no edges between any two elements. In the semi-streaming model, $G$ is…

Data Structures and Algorithms · Computer Science 2025-02-14 Daniel Ye

We study streaming algorithms for the maximum directed cut problem. The edges of an $n$-vertex directed graph arrive one by one in an arbitrary order, and the goal is to estimate the value of the maximum directed cut using a single pass and…

Data Structures and Algorithms · Computer Science 2026-04-01 Amir Azarmehr , Soheil Behnezhad , Shane Ferrante , Mohammad Saneian

Finding the $r\times r$ submatrix of maximum volume of a matrix $A\in\mathbb R^{n\times n}$ is an NP hard problem that arises in a variety of applications. We propose a new greedy algorithm of cost $\mathcal O(n)$, for the case $A$…

Numerical Analysis · Mathematics 2021-04-05 Stefano Massei

In the online sorting problem, we have an array $A$ of $n$ cells, and receive a stream of $n$ items $x_1,\dots,x_n\in [0,1]$. When an item arrives, we need to immediately and irrevocably place it into an empty cell. The goal is to minimize…

Data Structures and Algorithms · Computer Science 2025-10-23 Yang Hu

A streaming algorithm is considered to be adversarially robust if it provides correct outputs with high probability even when the stream updates are chosen by an adversary who may observe and react to the past outputs of the algorithm. We…

Data Structures and Algorithms · Computer Science 2021-09-24 Amit Chakrabarti , Prantar Ghosh , Manuel Stoeckl
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