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In this thesis, we develop various techniques for working with sets in machine learning. Each input or output is not an image or a sequence, but a set: an unordered collection of multiple objects, each object described by a feature vector.…

Machine Learning · Computer Science 2021-03-09 Yan Zhang

Object queries are essential in information seeking and decision making in vast areas of applications. However, a query may involve complex conditions on objects and sets, which can be arbitrarily nested and aliased. The objects and sets…

Programming Languages · Computer Science 2020-12-25 Yanhong A. Liu , Jon Brandvein , Scott D. Stoller , Bo Lin

We consider the robust version of items selection problem, in which the goal is to choose representatives from a family of sets, preserving constraints on the allowed items' combinations. We prove NP-hardness of the deterministic version,…

Discrete Mathematics · Computer Science 2019-07-23 Maciej Drwal

We consider the discrete assignment problem in which agents express ordinal preferences over objects and these objects are allocated to the agents in a fair manner. We use the stochastic dominance relation between fractional or randomized…

Computer Science and Game Theory · Computer Science 2015-06-18 Haris Aziz , Serge Gaspers , Simon Mackenzie , Toby Walsh

This paper argues that AI alignment is not merely difficult, but is founded on a fundamental logical contradiction. We first establish The Enumeration Paradox: we use machine learning precisely because we cannot enumerate all necessary…

Artificial Intelligence · Computer Science 2025-06-26 Jasper Yao

In this paper we focus our efforts on studying how a preorder and topology can be made compatible. Thus we provide a characterization of those that are continuous-compatible. Such a characterization states that such topologies must be finer…

Theoretical Economics · Economics 2024-02-06 Asier Estevan , Roberto Maura , Oscar Valero

This paper is devoted to the online dominating set problem and its variants. We believe the paper represents the first systematic study of the effect of two limitations of online algorithms: making irrevocable decisions while not knowing…

Data Structures and Algorithms · Computer Science 2018-09-14 Joan Boyar , Stephan J. Eidenbenz , Lene M. Favrholdt , Michal Kotrbčík , Kim S. Larsen

Given a dominating set, how much smaller a dominating set can we find through elementary operations? Here, we proceed by iterative vertex addition and removal while maintaining the property that the set forms a dominating set of bounded…

Discrete Mathematics · Computer Science 2020-05-06 Alexandre Blanché , Haruka Mizuta , Paul Ouvrard , Akira Suzuki

The stable marriage and stable roommates problems have been extensively studied due to their high applicability in various real-world scenarios. However, it might happen that no stable solution exists, or stable solutions do not meet…

Computer Science and Game Theory · Computer Science 2022-04-29 Kristóf Bérczi , Gergely Csáji , Tamás Király

Reconciling the tension between inductive learning and deductive reasoning in first-order relational domains is a longstanding challenge in AI. We study the problem of answering queries in a first-order relational probabilistic logic…

Artificial Intelligence · Computer Science 2026-02-17 Luise Ge , Brendan Juba , Kris Nilsson , Alison Shao

No feature ranking can be simultaneously faithful, stable, and complete when features are collinear. For collinear pairs, ranking reduces to a coin flip. We prove this impossibility, quantify it for four model classes, resolve it via…

Machine Learning · Computer Science 2026-05-22 Drake Caraker , Bryan Arnold , David Rhoads

Dependence logics are a modern family of logics of independence and dependence which mimic notions of database theory. In this paper, we aim to initiate the study of enumeration complexity in the field of dependence logics and thereby get a…

Logic in Computer Science · Computer Science 2018-03-13 Arne Meier , Christian Reinbold

Real-world applications of machine learning tools in high-stakes domains are often regulated to be fair, in the sense that the predicted target should satisfy some quantitative notion of parity with respect to a protected attribute.…

Machine Learning · Computer Science 2022-02-07 Han Zhao , Geoffrey J. Gordon

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

We consider linear orders of finite alternatives constructed by aggregating individual preferences. Specifically, we focus on linear orders that respect modified collective preference relations derived from supermajority rules, where…

Theoretical Economics · Economics 2025-04-01 Yasunori Okumura

The Assignment problem is a fundamental and well-studied problem in the intersection of Social Choice, Computational Economics and Discrete Allocation. In the Assignment problem, a group of agents expresses preferences over a set of items,…

Data Structures and Algorithms · Computer Science 2021-05-24 Barak Steindl , Meirav Zehavi

This paper studies the problem of finding the exact ranking from noisy comparisons. A comparison over a set of $m$ items produces a noisy outcome about the most preferred item, and reveals some information about the ranking. By repeatedly…

Machine Learning · Computer Science 2021-07-30 Wenbo Ren , Jia Liu , Ness B. Shroff

A central question in mathematics and computer science is the question of determining whether a given ideal $I$ is prime, which geometrically corresponds to the zero set of $I$, denoted $Z(I)$, being irreducible. The case of principal…

Computational Complexity · Computer Science 2025-03-27 Abhibhav Garg , Rafael Oliveira , Nitin Saxena

Arrow's Impossibility Theorem is a seminal result of Social Choice Theory that demonstrates the impossibility of ranked-choice decision-making processes to jointly satisfy a number of intuitive and seemingly desirable constraints. The…

Theoretical Economics · Economics 2026-04-07 Ori Livson , Mikhail Prokopenko

Many natural optimization problems derived from $\sf NP$ admit bilevel and multilevel extensions in which decisions are made sequentially by multiple players with conflicting objectives, as in interdiction, adversarial selection, and…

Computational Complexity · Computer Science 2026-02-16 Christoph Grüne , Berit Johannes , James B. Orlin , Lasse Wulf