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Many modern machine learning applications, such as multi-task learning, require finding optimal model parameters to trade-off multiple objective functions that may conflict with each other. The notion of the Pareto set allows us to focus on…

Optimization and Control · Mathematics 2022-09-05 Mao Ye , Qiang Liu

We study the problem of designing optimal auctions under restrictions on the set of permissible allocations. In addition to allowing us to restrict to deterministic mechanisms, we can also indirectly model non-additive valuations. We prove…

Computer Science and Game Theory · Computer Science 2016-06-07 Ian Kash , Rafael Frongillo

Designing fair algorithmic decision systems requires balancing model performance with fairness toward affected individuals: More fairness might require sacrificing some performance and vice versa, yet the space of possible trade-offs is…

Machine Learning · Computer Science 2026-05-12 Mieke Wilms , Christoph Heitz

In many real-world applications, the Pareto Set (PS) of a continuous multiobjective optimization problem can be a piecewise continuous manifold. A decision maker may want to find a solution set that approximates a small part of the PS and…

Neural and Evolutionary Computing · Computer Science 2024-04-02 Ping Guo , Qingfu Zhang , Xi Lin

We study the combinatorial pure exploration problem Best-Set in stochastic multi-armed bandits. In a Best-Set instance, we are given $n$ arms with unknown reward distributions, as well as a family $\mathcal{F}$ of feasible subsets over the…

Machine Learning · Computer Science 2017-06-06 Lijie Chen , Anupam Gupta , Jian Li , Mingda Qiao , Ruosong Wang

I provide a unified framework to establish the existence of a weak Pareto efficient, envy-free allocation in general settings: random allocations are probability measures on a compact metric space, and preferences of agents are represented…

Theoretical Economics · Economics 2026-05-28 Anna Vakarova

Many real-world decision-making problems involve optimizing multiple objectives simultaneously, rendering the selection of the most preferred solution a non-trivial problem: All Pareto optimal solutions are viable candidates, and it is…

Artificial Intelligence · Computer Science 2025-11-17 Niclas Boehmer , Maximilian T. Wittmann

We consider the division of a finite number of homogeneous divisible items among three players. Under the assumption that each player assigns a positive value to every item, we characterize the optimal allocations and we develop two exact…

Optimization and Control · Mathematics 2016-06-06 Marco Dall'Aglio , Camilla Di Luca , Lucia Milone

We study allocation problems without monetary transfers where agents have correlated types, i.e., hold private information about one another. Such peer information is relevant in various settings, including science funding, allocation of…

Theoretical Economics · Economics 2025-03-21 Axel Niemeyer , Justus Preusser

Optimization - minimization or maximization - in the lattice of subsets is a frequent operation in Artificial Intelligence tasks. Examples are subset-minimal model-based diagnosis, nonmonotonic reasoning by means of circumscription, or…

Artificial Intelligence · Computer Science 2016-12-23 Wolfgang Faber , Mauro Vallati , Federico Cerutti , Massimiliano Giacomin

The fair allocation of scarce resources is a central problem in mathematics, computer science, operations research, and economics. While much of the fair-division literature assumes that individuals have underlying cardinal preferences,…

Computer Science and Game Theory · Computer Science 2026-03-02 Trung Dang , Daniel Halpern , Anuran Makur , Alexandros Psomas , Japneet Singh , Paritosh Verma

The dominating set reconfiguration problem is defined as determining, for a given dominating set problem and two among its feasible solutions, whether one is reachable from the other via a sequence of feasible solutions subject to a certain…

Artificial Intelligence · Computer Science 2025-01-22 Masato Kato , Torsten Schaub , Takehide Soh , Naoyuki Tamura , Mutsunori Banbara

In multi-objective decision planning and learning, much attention is paid to producing optimal solution sets that contain an optimal policy for every possible user preference profile. We argue that the step that follows, i.e, determining…

Machine Learning · Computer Science 2018-02-22 Luisa M Zintgraf , Diederik M Roijers , Sjoerd Linders , Catholijn M Jonker , Ann Nowé

We study a fundamental fair allocation problem, where the agent's value is determined by the number of bins either used to pack or cover the items allocated to them. Fairness is evaluated using the maximin share (MMS) criterion. This…

Computer Science and Game Theory · Computer Science 2025-10-07 Bo Li , Ankang Sun , Zunyu Wang , Yu Zhou

Preordering is a generalization of clustering and partial ordering with applications in bioinformatics and social network analysis. Given a finite set $V$ and a value $c_{ab} \in \mathbb{R}$ for every ordered pair $ab$ of elements of $V$,…

Discrete Mathematics · Computer Science 2026-05-14 David Stein , Jannik Irmai , Bjoern Andres

The ranking problem is to order a collection of units by some unobserved parameter, based on observations from the associated distribution. This problem arises naturally in a number of contexts, such as business, where we may want to rank…

Methodology · Statistics 2016-10-28 Toby Kenney , Hao He , Hong Gu

This paper proposes an optimal allocation problem with ramified transport technology in a spatial economy. Ramified transportation is used to model the transport economy of scale in group transportation observed widely in both nature and…

Optimization and Control · Mathematics 2021-09-02 Qinglan Xia , Shaofeng Xu

In fair division of indivisible goods, using sequences of sincere choices (or picking sequences) is a natural way to allocate the objects. The idea is the following: at each stage, a designated agent picks one object among those that…

Computer Science and Game Theory · Computer Science 2016-04-07 Sylvain Bouveret , Michel Lemaître

In this paper we study combinatorial and algorithmic resp. complexity questions of upper domination, i.e., the maximum cardinality of a minimal dominating set in a graph. We give a full classification of the related maximisation and…

Many important stable matching problems are known to be NP-hard, even when strong restrictions are placed on the input. In this paper we seek to identify structural properties of instances of stable matching problems which will allow us to…

Computer Science and Game Theory · Computer Science 2018-12-14 Kitty Meeks , Baharak Rastegari