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We describe and analyse a simple greedy algorithm \2G\ that finds a good 2-matching $M$ in the random graph $G=G_{n,cn}^{\d\geq 3}$ when $c\geq 15$. A 2-matching is a spanning subgraph of maximum degree two and $G$ is drawn uniformly from…

Combinatorics · Mathematics 2011-08-09 Alan Frieze

The greedy sequential algorithm for maximal independent set (MIS) loops over the vertices in arbitrary order adding a vertex to the resulting set if and only if no previous neighboring vertex has been added. In this loop, as in many…

Data Structures and Algorithms · Computer Science 2012-02-16 Guy Blelloch , Jeremy Fineman , Julian Shun

We propose a Greedy strategy to solve the problem of Graph Cut, called GGC. It starts from the state where each data sample is regarded as a cluster and dynamically merges the two clusters which reduces the value of the global objective…

Machine Learning · Computer Science 2024-12-31 Feiping Nie , Shenfei Pei , Zengwei Zheng , Rong Wang , Xuelong Li

We study the greedy-based online algorithm for edge-weighted matching with (one-sided) vertex arrivals in bipartite graphs, and edge arrivals in general graphs. This algorithm was first studied more than a decade ago by Korula and P\'al for…

Data Structures and Algorithms · Computer Science 2021-12-28 Haim Kaplan , David Naori , Danny Raz

In the classic online graph balancing problem, edges arrive sequentially and must be oriented immediately upon arrival, to minimize the maximum in-degree. For adversarial arrivals, the natural greedy algorithm is $O(\log n)$-competitive,…

Data Structures and Algorithms · Computer Science 2026-04-07 Nikhil Bansal , Milind Prabhu , Sahil Singla , Siddharth M. Sundaram

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 use an entropy based method to study two graph maximization problems. We upper bound the number of matchings of fixed size $\ell$ in a $d$-regular graph on $N$ vertices. For $\frac{2\ell}{N}$ bounded away from 0 and 1, the logarithm of…

Combinatorics · Mathematics 2012-06-15 Teena Carroll , David Galvin , Prasad Tetali

We consider classes of objective functions of cardinality constrained maximization problems for which the greedy algorithm guarantees a constant approximation. We propose the new class of $\gamma$-$\alpha$-augmentable functions and prove…

Discrete Mathematics · Computer Science 2022-10-05 Yann Disser , David Weckbecker

In this paper we present a greedy algorithm for solving the problem of the maximum partitioning of graphs with supply and demand (MPGSD). The goal of the method is to solve the MPGSD for large graphs in a reasonable time limit. This is done…

Artificial Intelligence · Computer Science 2015-07-31 Raka Jovanovic , Abdelkader Bousselham , Stefan Voss

Let $r \ge 2$ be a fixed constant and let $ {\mathcal H}$ be an $r$-uniform, $D$-regular hypergraph on $N$ vertices. Assume further that $ D \to \infty$ as $N \to \infty$ and that degrees of pairs of vertices in ${\mathcal H}$ are at most…

Combinatorics · Mathematics 2019-10-09 Patrick Bennett , Tom Bohman

We prove a large deviation principle for a greedy exploration process on an Erd\"os-R\'enyi (ER) graph when the number of nodes goes to infinity. To prove our main result, we use the general strategy to study large deviations of processes…

Probability · Mathematics 2021-10-11 P. Bermolen , V. Goicoechea , M. Jonckheere , E. Mordecki

We propose a new yet natural algorithm for learning the graph structure of general discrete graphical models (a.k.a. Markov random fields) from samples. Our algorithm finds the neighborhood of a node by sequentially adding nodes that…

Machine Learning · Statistics 2012-02-09 Praneeth Netrapalli , Siddhartha Banerjee , Sujay Sanghavi , Sanjay Shakkottai

The greedy algorithm for approximating dominating sets is a simple method that is known to compute an $(\ln n+1)$-approximation of a minimum dominating set on any graph with $n$ vertices. We show that a small modification of the greedy…

Discrete Mathematics · Computer Science 2019-01-18 Sebastian Siebertz

MapReduce has become the de facto standard model for designing distributed algorithms to process big data on a cluster. There has been considerable research on designing efficient MapReduce algorithms for clustering, graph optimization, and…

Data Structures and Algorithms · Computer Science 2018-06-19 Nicholas J. A. Harvey , Christopher Liaw , Paul Liu

There has been a long history for studying randomized greedy matching algorithms since the work by Dyer and Frieze~(RSA 1991). We follow this trend and consider the problem formulated in the oblivious setting, in which the algorithm makes…

Data Structures and Algorithms · Computer Science 2020-03-10 Zhihao Gavin Tang , Xiaowei Wu , Yuhao Zhang

We revisit the complexity analysis of the recursive version of the randomized greedy algorithm for computing a maximal independent set (MIS), originally analyzed by Yoshida, Yamamoto, and Ito (2009). They showed that, on average per vertex,…

Data Structures and Algorithms · Computer Science 2026-04-03 Mina Dalirrooyfard , Konstantin Makarychev , Slobodan Mitrović

An unexpected difference between online and offline algorithms is observed. The natural greedy algorithms are shown to be worst case online optimal for Online Independent Set and Online Vertex Cover on graphs with 'enough' isolated…

Discrete Mathematics · Computer Science 2017-03-06 Joan Boyar , Christian Kudahl

Consider two ordered positive real number arrays of equal size. The problem is to find such set of indices of given size that the ratio of the sums of the array elements with those indices is minimized. In this work, in order to mitigate…

Combinatorics · Mathematics 2015-09-22 Alexander Lozovskiy

In large datasets, it is hard to discover and analyze structure. It is thus common to introduce tags or keywords for the items. In applications, such datasets are then filtered based on these tags. Still, even medium-sized datasets with a…

Machine Learning · Computer Science 2023-02-23 Dominik Dürrschnabel , Gerd Stumme

We implement and test the performances of several approximation algorithms for computing the minimum dominating set of a graph. These algorithms are the standard greedy algorithm, the recent LP rounding algorithms and a hybrid algorithm…

Data Structures and Algorithms · Computer Science 2020-09-11 Jonathan S. Li , Rohan Potru , Farhad Shahrokhi