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We study the oblivious matching problem, which aims at finding a maximum matching on a graph with unknown edge set. Any algorithm for the problem specifies an ordering of the vertex pairs. The matching is then produced by probing the pairs…

Data Structures and Algorithms · Computer Science 2020-02-17 Zhihao Gavin Tang , Xiaowei Wu , Yuhao Zhang

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

Matching, a task to optimally assign limited resources under constraints, is a fundamental technology for society. The task potentially has various objectives, conditions, and constraints; however, the efficient neural network architecture…

Machine Learning · Computer Science 2023-10-20 Shusaku Sone , Jiaxin Ma , Atsushi Hashimoto , Naoya Chiba , Yoshitaka Ushiku

Sampling without replacement is a natural online rounding strategy for converting fractional bipartite matching into an integral one. In Online Bipartite Matching, we can use the Balance algorithm to fractionally match each online vertex,…

Data Structures and Algorithms · Computer Science 2024-10-10 Zhiyi Huang , Chui Shan Lee , Jianqiao Lu , Xinkai Shu

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

Given a source of iid samples of edges of an input graph $G$ with $n$ vertices and $m$ edges, how many samples does one need to compute a constant factor approximation to the maximum matching size in $G$? Moreover, is it possible to obtain…

Data Structures and Algorithms · Computer Science 2019-07-15 Michael Kapralov , Slobodan Mitrović , Ashkan Norouzi-Fard , Jakab Tardos

In the online hypergraph matching problem, hyperedges of size $k$ over a common ground set arrive online in adversarial order. The goal is to obtain a maximum matching (disjoint set of hyperedges). A na\"ive greedy algorithm for this…

Data Structures and Algorithms · Computer Science 2024-02-15 Thorben Tröbst , Rajan Udwani

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

Greedy BST (or simply Greedy) is an online self-adjusting binary search tree defined in the geometric view ([Lucas, 1988; Munro, 2000; Demaine, Harmon, Iacono, Kane, Patrascu, SODA 2009). Along with Splay trees (Sleator, Tarjan 1985),…

Data Structures and Algorithms · Computer Science 2022-11-09 Parinya Chalermsook , Manoj Gupta , Wanchote Jiamjitrak , Nidia Obscura Acosta , Akash Pareek , Sorrachai Yingchareonthawornchai

We introduce a weighted version of the ranking algorithm by Karp et al. (STOC 1990), and prove a competitive ratio of 0.6534 for the vertex-weighted online bipartite matching problem when online vertices arrive in random order. Our result…

Data Structures and Algorithms · Computer Science 2019-09-13 Zhiyi Huang , Zhihao Gavin Tang , Xiaowei Wu , Yuhao Zhang

We study the classical, randomized Ranking algorithm which is known to be $(1 - \frac{1}{e})$-competitive in expectation for the Online Bipartite Matching Problem. We give a tail inequality bound, namely that Ranking is $(1 - \frac{1}{e} -…

Data Structures and Algorithms · Computer Science 2021-12-15 Milena Mihail , Thorben Tröbst

We consider a model for repeated stochastic matching where compatibility is probabilistic, is realized the first time agents are matched, and persists in the future. Such a model has applications in the gig economy, kidney exchange, and…

Computer Science and Game Theory · Computer Science 2021-06-15 Mobin Y. Jeloudar , Irene Lo , Tristan Pollner , Amin Saberi

We study partial and budgeted versions of the well studied connected dominating set problem. In the partial connected dominating set problem, we are given an undirected graph G = (V,E) and an integer n', and the goal is to find a minimum…

Data Structures and Algorithms · Computer Science 2013-11-12 Samir Khuller , Manish Purohit , Kanthi Sarpatwar

We study an online stochastic matching problem in which an algorithm sequentially matches $U$ users to $K$ arms, aiming to maximize cumulative reward over $T$ rounds under budget constraints. Without structural assumptions, computing the…

Machine Learning · Computer Science 2026-02-11 Omer Ben-Porat , Gur Keinan , Rotem Torkan

In the Online Machine Covering problem jobs, defined by their sizes, arrive one by one and have to be assigned to $m$ parallel and identical machines, with the goal of maximizing the load of the least-loaded machine. In this work, we study…

Data Structures and Algorithms · Computer Science 2021-10-28 Susanne Albers , Waldo Gálvez , Maximilian Janke

We introduce a new random input model for bipartite matching which we call the Random Type Poisson Arrival Model. Just like in the known i.i.d. model (introduced by Feldman et al. 2009), online nodes have types in our model. In contrast to…

Data Structures and Algorithms · Computer Science 2018-05-03 Allan Borodin , Christodoulos Karavasilis , Denis Pankratov

Several modern applications involve huge graphs and require fast answers to reachability queries. In more than two decades since first proposals, several approaches have been presented adopting on-line searches, hop labelling or transitive…

Data Structures and Algorithms · Computer Science 2016-11-09 Nicolas Boria , Gianpiero Cabodi , Paolo Camurati , Marco Palena , Paolo Pasini , Stefano Quer

In several applications of real-time matching of demand to supply in online marketplaces, the platform allows for some latency to batch the demand and improve the efficiency. Motivated by these applications, we study the optimal trade-off…

Data Structures and Algorithms · Computer Science 2022-12-01 Yiding Feng , Rad Niazadeh

Maximum cardinality matching in bipartite graphs is an important and well-studied problem. The fully dynamic version, in which edges are inserted and deleted over time has also been the subject of much attention. Existing algorithms for…

Data Structures and Algorithms · Computer Science 2015-08-18 Aaron Bernstein , Cliff Stein

We propose two one-pass streaming algorithms for the $\mathcal{NP}$-hard hypergraph matching problem. The first algorithm stores a small subset of potential matching edges in a stack using dual variables to select edges. It has an…

Data Structures and Algorithms · Computer Science 2025-07-09 Henrik Reinstädtler , S M Ferdous , Alex Pothen , Bora Uçar , Christian Schulz