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We present streaming algorithms for the graph $k$-matching problem in both the insert-only and dynamic models. Our algorithms, with space complexity matching the best upper bounds, have optimal or near-optimal update time, significantly…

Data Structures and Algorithms · Computer Science 2023-10-18 Jianer Chen , Qin Huang , Iyad Kanj , Qian Li , Ge Xia

In this note, we revisit the rounding algorithm of Wajc. Wajc gave a fully-adaptive randomized algorithm that rounds a dynamic fractional matching in an unweighted bipartite graph to an integral matching of nearly the same value in…

Data Structures and Algorithms · Computer Science 2024-02-06 Aditi Dudeja

Finding a maximum-cardinality or maximum-weight matching in (edge-weighted) undirected graphs is among the most prominent problems of algorithmic graph theory. For $n$-vertex and $m$-edge graphs, the best known algorithms run in…

Data Structures and Algorithms · Computer Science 2021-05-10 Tomohiro Koana , Viatcheslav Korenwein , André Nichterlein , Rolf Niedermeier , Philipp Zschoche

We present a work optimal algorithm for parallel fully batch-dynamic maximal matching against an oblivious adversary. It processes batches of updates (either insertions or deletions of edges) in constant expected amortized work per edge…

Data Structures and Algorithms · Computer Science 2025-10-24 Guy E. Blelloch , Andrew C. Brady

We present a new dynamic matching sparsification scheme. From this scheme we derive a framework for dynamically rounding fractional matchings against \emph{adaptive adversaries}. Plugging in known dynamic fractional matching algorithms into…

Data Structures and Algorithms · Computer Science 2020-06-17 David Wajc

Computing the Strongly-Connected Components (SCCs) in a graph $G=(V,E)$ is known to take only $O(m + n)$ time using an algorithm by Tarjan from 1972[SICOMP 72] where $m = |E|$, $n=|V|$. For fully-dynamic graphs, conditional lower bounds…

Data Structures and Algorithms · Computer Science 2019-03-15 Aaron Bernstein , Maximilian Probst , Christian Wulff-Nilsen

We consider the problem of maintaining a $(1-\epsilon)$-approximation to the densest subgraph (DSG) in an undirected multigraph as it undergoes edge insertions and deletions (the fully dynamic setting). Sawlani and Wang [SW20] developed a…

Data Structures and Algorithms · Computer Science 2022-10-07 Chandra Chekuri , Kent Quanrud

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

The goal in {\em reconfiguration problems} is to compute a {\em gradual transformation} between two feasible solutions of a problem such that all intermediate solutions are also feasible. In the {\em Matching Reconfiguration Problem} (MRP),…

Data Structures and Algorithms · Computer Science 2020-05-07 Noam Solomon , Shay Solomon

We study the approximate maximum weight matching (MWM) problem in a fully dynamic graph subject to edge insertions and deletions. We design meta-algorithms that reduce the problem to the unweighted approximate maximum cardinality matching…

Data Structures and Algorithms · Computer Science 2025-10-23 Aaron Bernstein , Jiale Chen

The field of dynamic graph algorithms aims at achieving a thorough understanding of real-world networks whose topology evolves with time. Traditionally, the focus has been on the classic sequential, centralized setting where the main…

Data Structures and Algorithms · Computer Science 2021-09-23 Shiri Antaki , Quanquan C. Liu , Shay Solomon

We study dynamic graph algorithms in the Massively Parallel Computation model, which was inspired by practical data processing systems. Our goal is to provide algorithms that can efficiently handle large batches of edge insertions and…

Data Structures and Algorithms · Computer Science 2021-01-12 Krzysztof Nowicki , Krzysztof Onak

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

We present a new approach for finding matchings in dense graphs by building on Szemer\'edi's celebrated Regularity Lemma. This allows us to obtain non-trivial albeit slight improvements over longstanding bounds for matchings in streaming…

Data Structures and Algorithms · Computer Science 2022-07-20 Sepehr Assadi , Soheil Behnezhad , Sanjeev Khanna , Huan Li

Random graph matching refers to recovering the underlying vertex correspondence between two random graphs with correlated edges; a prominent example is when the two random graphs are given by Erd\H{o}s-R\'{e}nyi graphs $G(n,\frac{d}{n})$.…

Machine Learning · Statistics 2020-07-21 Jian Ding , Zongming Ma , Yihong Wu , Jiaming Xu

We give two fully dynamic algorithms that maintain a $(1+\varepsilon)$-approximation of the weight $M$ of a minimum spanning forest (MSF) of an $n$-node graph $G$ with edges weights in $[1,W]$, for any $\varepsilon>0$. (1) Our deterministic…

Data Structures and Algorithms · Computer Science 2021-09-29 Monika Henzinger , Pan Peng

We consider the problem of computing a maximal matching with a distributed algorithm in the presence of batch-dynamic changes to the graph topology. We assume that a graph of $n$ nodes is vertex-partitioned among $k$ players that…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-30 Minming Li , Peter Robinson , Xianbin Zhu

Recently [Bhattacharya et al., STOC 2015] provide the first non-trivial algorithm for the densest subgraph problem in the streaming model with additions and deletions to its edges, i.e., for dynamic graph streams. They present a…

Data Structures and Algorithms · Computer Science 2015-07-30 Hossein Esfandiari , MohammadTaghi Hajiaghayi , David P. Woodruff

We propose a fast approximate algorithm for large graph matching. A new projected fixed-point method is defined and a new doubly stochastic projection is adopted to derive the algorithm. Previous graph matching algorithms suffer from high…

Computer Vision and Pattern Recognition · Computer Science 2012-08-13 Yao Lu , Kaizhu Huang , Cheng-Lin Liu

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