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In probably approximately correct (PAC) reinforcement learning (RL), an agent is required to identify an $\epsilon$-optimal policy with probability $1-\delta$. While minimax optimal algorithms exist for this problem, its instance-dependent…

Machine Learning · Computer Science 2022-10-25 Andrea Tirinzoni , Aymen Al-Marjani , Emilie Kaufmann

This thesis develops theoretical frameworks and algorithms that advance constrained reinforcement learning (RL) across control, preference learning, and alignment of large language models. The first contribution addresses constrained Markov…

Machine Learning · Computer Science 2025-12-12 Akhil Agnihotri

We discuss voting scenarios in which the set of voters (agents) and the set of alternatives are the same; that is, voters select a single representative from among themselves. Such a scenario happens, for instance, when a committee selects…

Computer Science and Game Theory · Computer Science 2019-07-23 Yakov Babichenko , Oren Dean , Moshe Tennenholtz

The electoral criterion of independence of irrelevant alternatives, or IIA, states that a voting system is unacceptable if it would choose a different winner if votes were recounted after one of the losers had dropped out. But IIA confuses…

Methodology · Statistics 2017-06-06 Richard B. Darlington

Many important quantities of interest are only partially identified from observable data: the data can limit them to a set of plausible values, but not uniquely determine them. This paper develops a unified framework for covariate-assisted…

Methodology · Statistics 2025-08-15 Eli Ben-Michael

We investigate approval-based committee voting with incomplete information about the approval preferences of voters. We consider several models of incompleteness where each voter partitions the set of candidates into approved, disapproved,…

Computer Science and Game Theory · Computer Science 2024-08-21 Aviram Imber , Jonas Israel , Markus Brill , Benny Kimelfeld

Condorcet's jury theorem states that the correct outcome is reached in direct majority voting systems with sufficiently large electorates as long as each voter's independent probability of voting for that outcome is greater than 0.5. Yet,…

Combinatorics · Mathematics 2023-01-10 Lucas Böttcher , Georgia Kernell

We study a generic framework that provides a unified view on two important classes of problems: (i) extensions of the k-median problem where clients are interested in having multiple facilities in their vicinity (e.g., due to the fact that,…

Data Structures and Algorithms · Computer Science 2018-03-13 Jarosław Byrka , Piotr Skowron , Krzysztof Sornat

Various algorithms for reinforcement learning (RL) exhibit dramatic variation in their convergence rates as a function of problem structure. Such problem-dependent behavior is not captured by worst-case analyses and has accordingly inspired…

Machine Learning · Statistics 2022-01-24 Koulik Khamaru , Eric Xia , Martin J. Wainwright , Michael I. Jordan

In the impartial selection problem, a subset of agents up to a fixed size $k$ among a group of $n$ is to be chosen based on votes cast by the agents themselves. A selection mechanism is impartial if no agent can influence its own chance of…

Computer Science and Game Theory · Computer Science 2024-08-06 Javier Cembrano , Svenja M. Griesbach , Maximilian J. Stahlberg

Perpetual voting was recently introduced as a framework for long-term collective decision making. In this framework, we consider a sequence of subsequent approval-based elections and try to achieve a fair overall outcome. To achieve…

Computer Science and Game Theory · Computer Science 2021-05-03 Martin Lackner , Jan Maly

Machine learning systems often experience a distribution shift between training and testing. In this paper, we introduce a simple variational objective whose optima are exactly the set of all representations on which risk minimizers are…

Machine Learning · Computer Science 2022-03-16 Yangjun Ruan , Yann Dubois , Chris J. Maddison

We define a family of runoff rules that work as follows: voters cast approval ballots over candidates; two finalists are selected; and the winner is decided by majority. With approval-type ballots, there are various ways to select the…

Computer Science and Game Theory · Computer Science 2023-01-27 Théo Delemazure , Jérôme Lang , Jean-François Laslier , Remzi M. Sanver

Approval-based committee voting has received significant attention in the social choice community. Among the studied rules, Thiele rules, and especially Proportional Approval Voting (PAV), stand out for desirable properties such as…

Artificial Intelligence · Computer Science 2026-05-11 Dimitris Avramidis , Alexandra Lassota , Ulrike Schmidt-Kraepelin , Adrian Vetta

In an approval-based committee election, the task is to select a committee of up to $k$ candidates from a set of $m$ candidates based on the preferences of $n$ voters, each of whom approves a subset of the candidates. A central open…

Computer Science and Game Theory · Computer Science 2026-05-08 Patrick Becker , Matthias Greger , Dominik Peters

We study two influential voting rules proposed in the 1890s by Phragm\'en and Thiele, which elect a committee or parliament of k candidates which proportionally represents the voters. Voters provide their preferences by approving an…

Computer Science and Game Theory · Computer Science 2022-11-01 Dominik Peters , Piotr Skowron

In this paper we develop a novel approach to relaxing Arrow's axioms for voting rules, addressing a long-standing critique in social choice theory. Classical axioms (often styled as fairness axioms or fairness criteria) are assessed in a…

Computer Science and Game Theory · Computer Science 2025-06-17 Suvadip Sana , Daniel Brous , Martin T. Wells , Moon Duchin

The Chamberlin-Courant and Monroe rules are fundamental and well-studied rules in the literature of multi-winner elections. The problem of determining if there exists a committee of size k that has a Chamberlin-Courant (respectively,…

Data Structures and Algorithms · Computer Science 2020-04-30 Chinmay Sonar , Palash Dey , Neeldhara Misra

Several important families of computational and statistical results in machine learning and randomized algorithms rely on uniform bounds on quadratic forms of random vectors or matrices. Such results include the Johnson-Lindenstrauss (J-L)…

Machine Learning · Computer Science 2019-12-06 Arindam Banerjee , Qilong Gu , Vidyashankar Sivakumar , Zhiwei Steven Wu

In the theory of voting, the Plurality rule for preferences that come in the form of linear orders selects the alternatives most frequently appearing in the first position of those orders, while the Anti-Plurality rule selects the…

Computer Science and Game Theory · Computer Science 2026-05-21 Ulle Endriss , Federico Fioravanti