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Related papers: A Collection of Lower Bounds for Online Matching o…

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For online matching with the line metric, we present a lower bound of $\Omega(\log n)$ on the approximation ratio of any online (possibly randomized) algorithm. This beats the previous best lower bound of $\Omega(\sqrt{\log n})$ and matches…

Data Structures and Algorithms · Computer Science 2021-08-23 Kangning Wang

In the classical Online Metric Matching problem, we are given a metric space with $k$ servers. A collection of clients arrive in an online fashion, and upon arrival, a client should irrevocably be matched to an as-yet-unmatched server. The…

Data Structures and Algorithms · Computer Science 2019-12-02 Varun Gupta , Ravishankar Krishnaswamy , Sai Sandeep

In the online sorting problem, a sequence of $n$ numbers in $[0, 1]$ (including $\{0,1\}$) have to be inserted in an array of size $m \ge n$ so as to minimize the sum of absolute differences between pairs of numbers occupying consecutive…

Data Structures and Algorithms · Computer Science 2025-08-21 Yossi Azar , Debmalya Panigrahi , Or Vardi

In online minimum cost matching on the line, $n$ requests appear one by one and have to be matched immediately and irrevocably to a given set of servers, all on the real line. The goal is to minimize the sum of distances from the requests…

Data Structures and Algorithms · Computer Science 2020-01-10 Nicole Megow , Lukas Nölke

We study the on-line minimum weighted bipartite matching problem in arbitrary metric spaces. Here, $n$ not necessary disjoint points of a metric space $M$ are given, and are to be matched on-line with $n$ points of $M$ revealed one by one.…

Data Structures and Algorithms · Computer Science 2007-06-06 Béla Csaba , András S. Pluhár

In the online metric bipartite matching problem, we are given a set $S$ of server locations in a metric space. Requests arrive one at a time, and on its arrival, we need to immediately and irrevocably match it to a server at a cost which is…

Computational Geometry · Computer Science 2018-03-21 Sharath Raghvendra

We study the minimum-cost metric perfect matching problem under online i.i.d arrivals. We are given a fixed metric with a server at each of the points, and then requests arrive online, each drawn independently from a known probability…

Data Structures and Algorithms · Computer Science 2019-04-22 Anupam Gupta , Guru Guruganesh , Binghui Peng , David Wajc

Online strategic classification studies settings in which agents strategically modify their features to obtain favorable predictions. For example, given a classifier that determines loan approval based on credit scores, applicants may open…

Machine Learning · Computer Science 2026-02-09 Chase Hutton , Adam Melrod , Han Shao

Motivated by the desire to utilize a limited number of configurable optical switches by recent advances in Software Defined Networks (SDNs), we define an online problem which we call the Caching in Matchings problem. This problem has a…

Data Structures and Algorithms · Computer Science 2024-02-26 Yaniv Sadeh , Haim Kaplan

Machine learning algorithms are designed to make accurate predictions of the future based on existing data, while online algorithms seek to bound some performance measure (typically the competitive ratio) without knowledge of the future.…

Machine Learning · Computer Science 2021-09-30 Kevin Rao

In the online metric matching problem, $n$ servers and $n$ requests lie in a metric space. Servers are available upfront, and requests arrive sequentially. An arriving request must be matched immediately and irrevocably to an available…

Data Structures and Algorithms · Computer Science 2026-04-22 Yingxi Li , Ellen Vitercik , Mingwei Yang

We study the online metric matching problem. There are $m$ servers and $n$ requests located in a metric space, where all servers are available upfront and requests arrive one at a time. Upon the arrival of a new request, it needs to be…

Data Structures and Algorithms · Computer Science 2025-10-16 Mingwei Yang , Sophie H. Yu

This paper studies the online scheduling problem of minimizing total flow time for $n$ jobs on $m$ identical machines. A classical $\Omega(n)$ lower bound shows that no deterministic single-machine algorithm can beat the trivial greedy,…

Data Structures and Algorithms · Computer Science 2026-04-02 Yutong Geng , Enze Sun , Zonghan Yang , Yuhao Zhang

We resolve a number of long-standing open problems in online graph coloring. More specifically, we develop tight lower bounds on the performance of online algorithms for fundamental graph classes. An important contribution is that our…

Data Structures and Algorithms · Computer Science 2017-07-04 Susanne Albers , Sebastian Schraink

We study the online traveling repairperson problem on a line within the recently proposed learning-augmented framework, which provides predictions on the requests to be served via machine learning. In the original model (with no…

Data Structures and Algorithms · Computer Science 2026-01-21 Swapnil Guragain , Gokarna Sharma

We consider the following fundamental routing problem. An adversary inputs packets arbitrarily at sources, each packet with an arbitrary destination. Traffic is constrained by link capacities and buffer sizes, and packets may be dropped at…

Data Structures and Algorithms · Computer Science 2015-01-27 Guy Even , Moti Medina , Boaz Patt-Shamir

In this paper, we study two variants of the online metric matching problem. The first problem is the online metric matching problem where all the servers are placed at one of two positions in the metric space. We show that a simple greedy…

Data Structures and Algorithms · Computer Science 2020-10-01 Toshiya Itoh , Shuichi Miyazaki , Makoto Satake

We revisit the online Unit Covering problem in higher dimensions: Given a set of $n$ points in $\mathbb{R}^d$, that arrive one by one, cover the points by balls of unit radius, so as to minimize the number of balls used. In this paper, we…

Computational Geometry · Computer Science 2018-08-29 Adrian Dumitrescu , Anirban Ghosh , Csaba D. Tóth

In the online sorting problem, we have an array $A$ of $n$ cells, and receive a stream of $n$ items $x_1,\dots,x_n\in [0,1]$. When an item arrives, we need to immediately and irrevocably place it into an empty cell. The goal is to minimize…

Data Structures and Algorithms · Computer Science 2025-10-23 Yang Hu

We consider the problem of online Min-cost Perfect Matching with Delays (MPMD) introduced by Emek et al. (STOC 2016). In this problem, an even number of requests appear in a metric space at different times and the goal of an online…

Data Structures and Algorithms · Computer Science 2017-04-25 Marcin Bienkowski , Artur Kraska , Paweł Schmidt
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