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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

We study the problem of allocating indivisible items to budget-constrained agents, aiming to provide fairness and efficiency guarantees. Specifically, our goal is to ensure that the resulting allocation is envy-free up to any item (EFx)…

Computer Science and Game Theory · Computer Science 2023-08-04 Marius Garbea , Vasilis Gkatzelis , Xizhi Tan

We investigate the problem of approximating an incomplete preference relation $\succsim$ on a finite set by a complete preference relation. We aim to obtain this approximation in such a way that the choices on the basis of two preferences,…

Theoretical Economics · Economics 2023-11-14 Hiroki Nishimura , Efe A. Ok

Consider the problem of constructing an experimental design, optimal for estimating parameters of a given statistical model with respect to a chosen criterion. To address this problem, the literature usually provides a single solution.…

Computation · Statistics 2024-11-05 Radoslav Harman , Lenka Filová , Samuel Rosa

Diversity maximization problem is a well-studied problem where the goal is to find $k$ diverse items. Fair diversity maximization aims to select a diverse subset of $k$ items from a large dataset, while requiring that each group of items be…

Data Structures and Algorithms · Computer Science 2025-06-11 Florian Adriaens , Nikolaj Tatti

Randomized mechanisms, which map a set of bids to a probability distribution over outcomes rather than a single outcome, are an important but ill-understood area of computational mechanism design. We investigate the role of randomized…

Computer Science and Game Theory · Computer Science 2009-04-17 Patrick Briest , Shuchi Chawla , Robert Kleinberg , S. Matthew Weinberg

We consider the problem of fair allocation of indivisible items to agents that have arbitrary entitlements to the items. Every agent $i$ has a valuation function $v_i$ and an entitlement $b_i$, where entitlements sum up to~1. Which…

Computer Science and Game Theory · Computer Science 2024-05-24 Moshe Babaioff , Uriel Feige

Scalable real-time assortment optimization has become essential in e-commerce operations due to the need for personalization and the availability of a large variety of items. While this can be done when there are simplistic assortment…

Artificial Intelligence · Computer Science 2021-03-03 Theja Tulabandhula , Deeksha Sinha , Saketh Karra

We define a general method for finding a quasi-best approximant in sup-norm to a target density belonging to a given model, based on independent samples drawn from distributions which average to the target (which does not necessarily belong…

Statistics Theory · Mathematics 2025-06-26 Guillaume Maillard

This paper studies an optimal consensus problem for a group of heterogeneous high-order agents with unknown control directions. Compared with existing consensus results, the consensus point is further required to an optimal solution to some…

Optimization and Control · Mathematics 2020-07-28 Yutao Tang

We consider the problem of designing a revenue-maximizing auction for a single item, when the values of the bidders are drawn from a correlated distribution. We observe that there exists an algorithm that finds the optimal randomized…

Computer Science and Game Theory · Computer Science 2015-03-17 Shahar Dobzinski , Hu Fu , Robert Kleinberg

We study the fair allocation problem of indivisible items with subsidy. In this paper, we focus on the notion of fairness - equitability (EQ), which requires that items be allocated such that all agents value the bundle they receive…

Computer Science and Game Theory · Computer Science 2025-09-10 Yuanyuan Wang , Tianze Wei

We aim to create the highest possible quality of treatment-control matches for categorical data in the potential outcomes framework. Matching methods are heavily used in the social sciences due to their interpretability, but most matching…

Machine Learning · Statistics 2019-06-11 Yameng Liu , Aw Dieng , Sudeepa Roy , Cynthia Rudin , Alexander Volfovsky

We investigate the mechanism design problem faced by a principal who hires \emph{multiple} agents to gather and report costly information. Then, the principal exploits the information to make an informed decision. We model this problem as a…

Computer Science and Game Theory · Computer Science 2023-07-13 Federico Cacciamani , Matteo Castiglioni , Nicola Gatti

We study a fair division problem with indivisible items, namely the computation of maximin share allocations. Given a set of $n$ players, the maximin share of a single player is the best she can guarantee to herself, if she would partition…

Computer Science and Game Theory · Computer Science 2016-05-16 Georgios Amanatidis , Georgios Birmpas , Evangelos Markakis

We study an abstract optimal auction problem for a single good or service. This problem includes environments where agents have budgets, risk preferences, or multi-dimensional preferences over several possible configurations of the good…

Computer Science and Game Theory · Computer Science 2012-03-23 Saeed Alaei , Hu Fu , Nima Haghpanah , Jason Hartline , Azarakhsh Malekian

We consider the problem of approximate maximin share (MMS) allocation of indivisible items among three agents with additive valuation functions. For goods, we show that an $\frac{11}{12}$ - MMS allocation always exists, improving over the…

Computer Science and Game Theory · Computer Science 2022-05-12 Uriel Feige , Alexey Norkin

As we all know, users and item-providers are two main parties of participants in recommender systems. However, most existing research efforts on recommendation were focused on better serving users and overlooked the purpose of…

Information Retrieval · Computer Science 2021-10-22 Qiang Dong , Shuang-Shuang Xie , Wen-Jun Li

We study the design of a decentralized two-sided matching market in which agents' search is guided by the platform. There are finitely many agent types, each with (potentially random) preferences drawn from known type-specific…

Computer Science and Game Theory · Computer Science 2021-08-19 Nicole Immorlica , Brendan Lucier , Vahideh Manshadi , Alexander Wei

Many multiagent tasks -- such as reviewer assignment, coalition formation, or fair resource allocation -- require selecting a group of agents such that collaboration remains effective even in the worst case. The \emph{weighted max-min…

Data Structures and Algorithms · Computer Science 2026-02-10 Sharareh Alipour
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