The paper studies online resource allocation in non‑profit settings, focusing on internal equity among homogeneous requesters who differ in demographic attributes such as race, gender, and age. It proposes two linear‑programming based sampling algorithms designed to ensure each demographic group receives a share of resources proportional to a preset target ratio. The authors evaluate the algorithms theoretically via competitive‑ratio analysis and empirically using real COVID‑19 vaccination data from Minnesota, demonstrating that the strategies effectively promote equity, particularly when the arrival population is disproportionately represented.
By Pan Xu, Yifan Xu
The paper studies a budget‑constrained welfare problem for pooled testing, where agents have heterogeneous utilities and independent probabilities of being healthy. It proves that an optimal dynamic testing policy can achieve at most twice the welfare of the best static overlapping allocation, regardless of population, budget, or pool‑size limit. The authors also identify cases where adaptivity offers no benefit, show that re‑pooling after positive tests is necessary for strict gains, and provide approximation guarantees for greedy algorithms.
By Edwin Lock, Nicholas Lopez, Francisco Marmolejo-Coss\'io, Jose Roberto Tello Ayala, David C. Parkes
arXiv:2607. 23310v1 Announce Type: cross Abstract: We study an online variant of discrete fair division under generalized assignment budget constraints.
By Saar Cohen, Nicholas Teh, Paul W. Goldberg, Michael J. Wooldridge
arXiv:2609. 29958v1 Announce Type: cross Abstract: We study a matching mechanism where agents and objects are described by features rather than complete rankings.
By Irene Aldridge
arXiv:2606. 18679v1 Announce Type: cross Abstract: We study the problem of fair online resource allocation, motivated by applications such as refugee resettlement and airline scheduling, where agents arrive sequentially and must be assigned to facilities with limited capacities.
By Christopher En, Yuri Faenza, Andrea Lodi, Gonzalo Mu\~noz
arXiv:2507. 09473v2 Announce Type: replace-cross Abstract: We study the dynamic allocation of indivisible resources to strategic agents under long-term constraints, where the planner aims to maximize social welfare, satisfy multiple constraints, and elicit near-truthful reports.
By Yan Dai, Negin Golrezaei, Patrick Jaillet
arXiv:2607. 26485v1 Announce Type: cross Abstract: Resource allocation across multiple agent groups arises in many applications including e-commerce recommendation systems, housing assignment, and course allocation, and is commonly formulated as an optimization problem with diversity constraints to ensure group fairness.
By Keke Huang, Yik Yu Ng, Laks V. S. Lakshmanan, Xiaokui Xiao
The paper investigates regression when outcomes are observed only after passing through selection filters that depend on both covariates and outcomes, a common issue in fields such as clinical trials, labor markets, and auctions. It provides a complete characterization of the minimal assumptions on the functional forms of selection processes that allow regression to remain possible, and shows that the regression function can sometimes be identified even when the selection filter itself cannot. Under stronger identification conditions, the authors also deliver finite‑sample estimation guarantees, explicit convergence rates, and oracle‑efficient algorithms, offering the first general‑purpose estimation method for this broad class of selection problems.
By Vikram Kher, Jane H. Lee, Anay Mehrotra, Manolis Zampetakis
arXiv:2606. 19883v1 Announce Type: new Abstract: We study a multi-agent multi-armed bandit problem in the competitive setup with two-sided matching markets under a human centric decision making model.
By Ananya Kunisetty, Avishek Ghosh
arXiv:2606. 13201v1 Announce Type: new Abstract: Human decision-making often involves choosing between multi-attribute alternatives, yet classical models assume fully compensatory utility aggregation despite evidence that people reject options with poor performance on critical attributes.
By Manisha Dubey, Anirban Sarkar, Subramanian Ramamoorthy
arXiv:2607. 23367v1 Announce Type: cross Abstract: We study whether strictly positive marginal values restore the compatibility of envy-freeness up to one good (EF1) and Pareto optimality (PO) for indivisible goods.
By Nicholas Teh
arXiv:2406. 12413v3 Announce Type: replace-cross Abstract: We study the problem of allocating a set of indivisible goods to a set of agents with additive valuation functions, aiming to achieve approximate envy-freeness up to any good ($\alpha$-EFX).
By Georgios Amanatidis, Aris Filos-Ratsikas, Alkmini Sgouritsa