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We consider the setting of online computation with advice, and study the bin packing problem and a number of scheduling problems. We show that it is possible, for any of these problems, to arbitrarily approach a competitive ratio of $1$…

Data Structures and Algorithms · Computer Science 2015-08-06 Marc P. Renault , Adi Rosén , Rob van Stee

We study a fundamental model of online preference aggregation, where an algorithm maintains an ordered list of $n$ elements. An input is a stream of preferred sets $R_1, R_2, \dots, R_t, \dots$. Upon seeing $R_t$ and without knowledge of…

Data Structures and Algorithms · Computer Science 2023-03-28 Marcin Bienkowski , Marcin Mucha

We consider the matching problem on the line with advice complexity. We give a 1-competitive online algorithm with advice complexity $n-1,$ and show that there is no 1-competitive online algorithm reading less than $n-1$ bits of advice.…

Data Structures and Algorithms · Computer Science 2024-12-11 Béla Csaba , Judit Nagy-György

In the online bipartite matching problem with replacements, all the vertices on one side of the bipartition are given, and the vertices on the other side arrive one by one with all their incident edges. The goal is to maintain a maximum…

Data Structures and Algorithms · Computer Science 2018-05-07 Aaron Bernstein , Jacob Holm , Eva Rotenberg

In many sequential decision making applications, the change of decision would bring an additional cost, such as the wear-and-tear cost associated with changing server status. To control the switching cost, we introduce the problem of online…

Machine Learning · Computer Science 2021-03-23 Guanghui Wang , Yuanyu Wan , Tianbao Yang , Lijun Zhang

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

In the online bipartite matching with reassignments problem, an algorithm is initially given only one side of the vertex set of a bipartite graph; the vertices on the other side are revealed to the algorithm one by one, along with its…

Data Structures and Algorithms · Computer Science 2020-03-12 Yongho Shin , Kangsan Kim , Seungmin Lee , Hyung-Chan An

Motivated by fairness requirements in communication networks, we introduce a natural variant of the online paging problem, called \textit{min-max} paging, where the objective is to minimize the maximum number of faults on any page. While…

Data Structures and Algorithms · Computer Science 2022-12-07 Ashish Chiplunkar , Monika Henzinger , Sagar Sudhir Kale , Maximilian Vötsch

Online load balancing for heterogeneous machines aims to minimize the makespan (maximum machine workload) by scheduling arriving jobs with varying sizes on different machines. In the adversarial setting, where an adversary chooses not only…

Data Structures and Algorithms · Computer Science 2024-05-22 Sungjin Im , Ravi Kumar , Shi Li , Aditya Petety , Manish Purohit

In this paper we study the mincut problem in the online setting. We consider two distinct models: A) competitive analysis and B) regret analysis. In the competitive setting we consider the vertex arrival model; whenever a new vertex arrives…

Data Structures and Algorithms · Computer Science 2020-08-17 Avah Banerjee , Guoli Ding

The online bisection problem requires maintaining a dynamic partition of $n$ nodes into two equal-sized clusters. Requests arrive sequentially as node pairs. If the nodes lie in different clusters, the algorithm pays unit cost. After each…

Data Structures and Algorithms · Computer Science 2026-02-12 Mateusz Basiak , Marcin Bienkowski , Guy Even , Agnieszka Tatarczuk

We consider online algorithms under both the competitive ratio criteria and the regret minimization one. Our main goal is to build a unified methodology that would be able to guarantee both criteria simultaneously. For a general class of…

Machine Learning · Computer Science 2019-04-09 Amit Daniely , Yishay Mansour

In the problem of online unweighted interval selection, the objective is to maximize the number of non-conflicting intervals accepted by the algorithm. In the conventional online model of irrevocable decisions, there is an Omega(n) lower…

Data Structures and Algorithms · Computer Science 2025-06-03 Allan Borodin , Christodoulos Karavasilis

Online advertising has recently grown into a highly competitive and complex multi-billion-dollar industry, with advertisers bidding for ad slots at large scales and high frequencies. This has resulted in a growing need for efficient…

Machine Learning · Computer Science 2023-07-04 Zhe Feng , Swati Padmanabhan , Di Wang

We study online convex optimization in a setting where the learner seeks to minimize the sum of a per-round hitting cost and a movement cost which is incurred when changing decisions between rounds. We prove a new lower bound on the…

Machine Learning · Computer Science 2019-10-23 Gautam Goel , Yiheng Lin , Haoyuan Sun , Adam Wierman

We study the online variant of the Min-Sum Set Cover (MSSC) problem, a generalization of the well-known list update problem. In the MSSC problem, an algorithm has to maintain the time-varying permutation of the list of $n$ elements, and…

Data Structures and Algorithms · Computer Science 2023-07-03 Mateusz Basiak , Marcin Bienkowski , Agnieszka Tatarczuk

Online linear programming (OLP) has found broad applications in revenue management and resource allocation. State-of-the-art OLP algorithms achieve low regret by repeatedly solving linear programming (LP) subproblems that incorporate…

Machine Learning · Statistics 2025-11-04 Jingruo Sun , Wenzhi Gao , Ellen Vitercik , Yinyu Ye

This paper provides threshold policies with tight guarantees for online selection with convex cost (OSCC). In OSCC, a seller wants to sell some asset to a sequence of buyers with the goal of maximizing her profit. The seller can produce…

Computer Science and Game Theory · Computer Science 2024-01-24 Xiaoqi Tan , Siyuan Yu , Raouf Boutaba , Alberto Leon-Garcia

We study a two-sided market, wherein, price-sensitive heterogeneous customers and servers arrive and join their respective queues. A compatible customer-server pair can then be matched by the platform, at which point, they leave the system.…

Machine Learning · Computer Science 2025-10-17 Zixian Yang , Sushil Mahavir Varma , Lei Ying

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