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We study the $k$-connectivity augmentation problem ($k$-CAP) in the single-pass streaming model. Given a $(k-1)$-edge connected graph $G=(V,E)$ that is stored in memory, and a stream of weighted edges $L$ with weights in $\{0,1,\dots,W\}$,…

Data Structures and Algorithms · Computer Science 2024-02-19 Ce Jin , Michael Kapralov , Sepideh Mahabadi , Ali Vakilian

Graphs provide a natural way to represent data by encoding information about objects and the relationships between them. With the ever-increasing amount of data collected and generated, locating specific patterns of relationships between…

Data Structures and Algorithms · Computer Science 2026-04-28 Tatyana Benko , Rebecca Jones , Lucas Tate

We study the fully dynamic maximum matching problem. In this problem, the goal is to efficiently maintain an approximate maximum matching of a graph that is subject to edge insertions and deletions. Our focus is on algorithms that maintain…

Data Structures and Algorithms · Computer Science 2024-09-26 Soheil Behnezhad , Alma Ghafari

Let $G=(V, E)$ be a given edge-weighted graph and let its {\em realization} $\mathcal{G}$ be a random subgraph of $G$ that includes each edge $e \in E$ independently with probability $p$. In the {\em stochastic matching} problem, the goal…

Data Structures and Algorithms · Computer Science 2020-04-21 Soheil Behnezhad , Mahsa Derakhshan

We study the communication complexity and streaming complexity of approximating unweighted semi-matchings. A semi-matching in a bipartite graph G = (A, B, E), with n = |A|, is a subset of edges S that matches all A vertices to B vertices…

Data Structures and Algorithms · Computer Science 2013-04-26 Christian Konrad , Adi Rosén

Detecting and visualizing what are the most relevant changes in an evolving network is an open challenge in several domains. We present a fast algorithm that filters subsets of the strongest nodes and edges representing an evolving weighted…

Social and Information Networks · Computer Science 2014-11-05 Przemyslaw A. Grabowicz , Luca Maria Aiello , Filippo Menczer

We give the first fully dynamic algorithm which maintains a $(1-\epsilon)$-approximate densest subgraph in worst-case time $\text{poly}(\log n, \epsilon^{-1})$ per update. Dense subgraph discovery is an important primitive for many…

Data Structures and Algorithms · Computer Science 2020-03-12 Saurabh Sawlani , Junxing Wang

We give a combinatorial algorithm for computing exact maximum flows in directed graphs with $n$ vertices and edge capacities from $\{1,\dots,U\}$ in $\tilde{O}(n^{2}\log U)$ time, which is near-optimal on dense graphs. This shaves an…

Data Structures and Algorithms · Computer Science 2025-10-21 Aaron Bernstein , Joakim Blikstad , Jason Li , Thatchaphol Saranurak , Ta-Wei Tu

We study sublinear time algorithms for estimating the size of maximum matching in graphs. Our main result is a $(\frac{1}{2}+\Omega(1))$-approximation algorithm which can be implemented in $O(n^{1+\epsilon})$ time, where $n$ is the number…

Data Structures and Algorithms · Computer Science 2022-06-28 Soheil Behnezhad , Mohammad Roghani , Aviad Rubinstein , Amin Saberi

We revisit the MaxSAT problem in the data stream model. In this problem, the stream consists of $m$ clauses that are disjunctions of literals drawn from $n$ Boolean variables. The objective is to find an assignment to the variables that…

Data Structures and Algorithms · Computer Science 2022-08-22 Hoa T. Vu

In this paper we consider graph algorithms in models of computation where the space usage (random accessible storage, in addition to the read only input) is sublinear in the number of edges $m$ and the access to input data is constrained.…

Data Structures and Algorithms · Computer Science 2015-04-21 Kook Jin Ahn , Sudipto Guha

Graph matching, also known as network alignment, refers to finding a bijection between the vertex sets of two given graphs so as to maximally align their edges. This fundamental computational problem arises frequently in multiple fields…

Data Structures and Algorithms · Computer Science 2021-08-10 Cheng Mao , Mark Rudelson , Konstantin Tikhomirov

We present a randomized augmenting paths-based algorithm to compute the maximum flow in a directed, uncapacitated graph in almost $m+nF$ time, matching the algorithm of Karger and Levine for undirected graphs (SICOMP 2015). Combined with an…

Data Structures and Algorithms · Computer Science 2026-04-17 Jason Li

We consider communication-efficient weighted and unweighted (uniform) random sampling from distributed data streams presented as a sequence of mini-batches of items. This is a natural model for distributed streaming computation, and our…

Data Structures and Algorithms · Computer Science 2020-02-26 Lorenz Hübschle-Schneider , Peter Sanders

We study learning-augmented streaming algorithms for estimating the value of MAX-CUT in a graph. In the classical streaming model, while a $1/2$-approximation for estimating the value of MAX-CUT can be trivially achieved with $O(1)$ words…

Data Structures and Algorithms · Computer Science 2025-01-07 Yinhao Dong , Pan Peng , Ali Vakilian

We study the problem of estimating the number of triangles in a graph stream. No streaming algorithm can get sublinear space on all graphs, so methods in this area bound the space in terms of parameters of the input graph such as the…

Data Structures and Algorithms · Computer Science 2019-04-18 John Kallaugher , Eric Price

In this paper we study maximum size and minimum weight planar matchings of inhomogenous random bipartite graphs. Our motivation for this study comes from efficient usage of cross edges in relay networks for overall improvement in network…

Probability · Mathematics 2025-04-10 Ghurumuruhan Ganesan

In this paper we study dynamic averaging load balancing on general graphs. We consider infinite time and dynamic processes, where in every step new load items are assigned to randomly chosen nodes. A matching is chosen, and the load is…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-02-24 Petra Berenbrink , Lukas Hintze , Hamed Hosseinpour , Dominik Kaaser , Malin Rau

In the semi-streaming model, an algorithm receives a stream of edges of a graph in arbitrary order and uses a memory of size $O(n \mbox{ polylog } n)$, where $n$ is the number of vertices of a graph. In this work, we present semi-streaming…

Data Structures and Algorithms · Computer Science 2014-04-11 Christian Konrad , Frédéric Magniez , Claire Mathieu

Finding dense subgraphs is a fundamental problem with applications to community detection, clustering, and data mining. Our work focuses on finding approximate densest subgraphs in directed graphs in computational models for processing…

Data Structures and Algorithms · Computer Science 2025-09-29 Slobodan Mitrović , Theodore Pan , Mahdi Qaempanah , Mohammad Amin Raeisi
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