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Related papers: Greedy Matching: Guarantees and Limitations

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In this paper, we study Ranking, a well-known randomized greedy matching algorithm, for general graphs. The algorithm was originally introduced by Karp, Vazirani, and Vazirani [STOC 1990] for the online bipartite matching problem with…

Data Structures and Algorithms · Computer Science 2025-11-11 Mahsa Derakhshan , Mohammad Roghani , Mohammad Saneian , Tao Yu

Closeness is a widely-used centrality measure in social network analysis. For a node it indicates the reciprocal of the average shortest-path distance to the other nodes of the network. While the identification of the k nodes with highest…

Data Structures and Algorithms · Computer Science 2019-05-16 Elisabetta Bergamini , Tanya Gonser , Henning Meyerhenke

Motivated by online advertisement and exchange settings, greedy randomized algorithms for the maximum matching problem have been studied, in which the algorithm makes (random) decisions that are essentially oblivious to the input graph. Any…

Data Structures and Algorithms · Computer Science 2013-07-12 T-H. Hubert Chan , Fei Chen , Xiaowei Wu , Zhichao Zhao

A deterministic approximation algorithm is presented for the maximization of non-monotone submodular functions over a ground set of size $n$ subject to cardinality constraint $k$; the algorithm is based upon the idea of interlacing two…

Data Structures and Algorithms · Computer Science 2019-10-28 Alan Kuhnle

A $k$-submodular function naturally generalizes submodular functions by taking as input $k$ disjoint subsets, rather than a single subset. Unlike standard submodular maximization, which only requires selecting elements for the solution,…

Data Structures and Algorithms · Computer Science 2025-07-18 Chenhao Wang

Motivated by Internet targeted advertising, we address several ad allocation problems. Prior work has established these problems admit no randomized online algorithm better than $(1-\frac{1}{e})$-competitive…

Data Structures and Algorithms · Computer Science 2015-04-30 Joseph , Naor , David Wajc

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 study the average performance of online greedy matching algorithms on $G(n,n,p)$, the random bipartite graph with $n$ vertices on each side and edges occurring independently with probability $p=p(n)$. In the online model, vertices on one…

Data Structures and Algorithms · Computer Science 2013-07-10 Andrew Mastin , Patrick Jaillet

We study the problem of maximizing a submodular function, subject to a cardinality constraint, with a set of agents communicating over a connected graph. We propose a distributed greedy algorithm that allows all the agents to converge to a…

Optimization and Control · Mathematics 2020-09-29 Lintao Ye , Shreyas Sundaram

The greedy algorithm for monotone submodular function maximization subject to cardinality constraint is guaranteed to approximate the optimal solution to within a $1-1/e$ factor. Although it is well known that this guarantee is essentially…

Data Structures and Algorithms · Computer Science 2022-02-15 Aviad Rubinstein , Junyao Zhao

Submodular maximization with a cardinality constraint can model various problems, and those problems are often very large in practice. For the case where objective functions are monotone, many fast approximation algorithms have been…

Data Structures and Algorithms · Computer Science 2020-01-13 Shinsaku Sakaue

A bipartite graph $G(U,V;E)$ that admits a perfect matching is given. One player imposes a permutation $\pi$ over $V$, the other player imposes a permutation $\sigma$ over $U$. In the greedy matching algorithm, vertices of $U$ arrive in…

Computer Science and Game Theory · Computer Science 2018-03-16 Alon Eden , Uriel Feige , Michal Feldman

Given the proximity of many wireless users and their diversity in consuming local resources (e.g., data-plans, computation and energy resources), device-to-device (D2D) resource sharing is a promising approach towards realizing a sharing…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-23 Shuqin Gao , Costas A. Courcoubetis , Lingjie Duan

Given the proximity of many wireless users and their diversity in consuming local resources (e.g., data-plans, computation and even energy resources), device-to-device (D2D) resource sharing is a promising approach towards realizing a…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-02 Shuqin Gao , Costas Courcoubetis , Lingjie Duan

Motivated by a wide range of applications in data mining and machine learning, we consider the problem of maximizing a submodular function subject to supermodular cost constraints. In contrast to the well-understood setting of cardinality…

Data Structures and Algorithms · Computer Science 2026-02-19 Ajitesh Srivastava , Shanghua Teng

Is it possible to maximize a monotone submodular function faster than the widely used lazy greedy algorithm (also known as accelerated greedy), both in theory and practice? In this paper, we develop the first linear-time algorithm for…

Machine Learning · Computer Science 2014-12-01 Baharan Mirzasoleiman , Ashwinkumar Badanidiyuru , Amin Karbasi , Jan Vondrak , Andreas Krause

In this paper, we study the non-monotone adaptive submodular maximization problem subject to a cardinality constraint. We first revisit the adaptive random greedy algorithm proposed in \citep{gotovos2015non}, where they show that this…

Machine Learning · Computer Science 2020-12-16 Shaojie Tang

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

Wattenhofer [WW04] derive a complicated distributed algorithm to compute a weighted matching of an arbitrary weighted graph, that is at most a factor 5 away from the maximum weighted matching of that graph. We show that a variant of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Jaap-Henk Hoepman

It is known that greedy methods perform well for maximizing monotone submodular functions. At the same time, such methods perform poorly in the face of non-monotonicity. In this paper, we show - arguably, surprisingly - that invoking the…

Machine Learning · Computer Science 2017-04-07 Moran Feldman , Christopher Harshaw , Amin Karbasi