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Meta-analysis is an important tool for combining results from multiple studies and has been widely used in evidence-based medicine for several decades. This paper reports, for the first time, an interesting and valuable paradox in…

Applications · Statistics 2019-05-15 Jiandong Shi , Aimin Wu , Tiejun Tong

The wisdom of the crowd has long become the de facto approach for eliciting information from individuals or experts in order to predict the ground truth. However, classical democratic approaches for aggregating individual \emph{votes} only…

Computer Science and Game Theory · Computer Science 2021-05-21 Hadi Hosseini , Debmalya Mandal , Nisarg Shah , Kevin Shi

Multiwinner voting rules are used to select a small representative subset of candidates or items from a larger set given the preferences of voters. However, if candidates have sensitive attributes such as gender or ethnicity (when selecting…

Computers and Society · Computer Science 2018-06-20 L. Elisa Celis , Lingxiao Huang , Nisheeth K. Vishnoi

Election control considers the problem of an adversary who attempts to tamper with a voting process, in order to either ensure that their favored candidate wins (constructive control) or another candidate loses (destructive control). As…

Multiagent Systems · Computer Science 2017-11-27 Bryan Wilder , Yevgeniy Vorobeychik

Apportionment is the act of distributing the seats of a legislature among political parties (or states) in proportion to their vote shares (or populations). A famous impossibility by Balinski and Young (2001) shows that no apportionment…

Computer Science and Game Theory · Computer Science 2024-05-07 José Correa , Paul Gölz , Ulrike Schmidt-Kraepelin , Jamie Tucker-Foltz , Victor Verdugo

Inverse Reinforcement Learning (IRL) -- the problem of learning reward functions from demonstrations of an \emph{expert policy} -- plays a critical role in developing intelligent systems. While widely used in applications, theoretical…

Machine Learning · Statistics 2024-02-13 Lei Zhao , Mengdi Wang , Yu Bai

The computational study of elections generally assumes that the preferences of the electorate come in as a list of votes. Depending on the context, it may be much more natural to represent the list succinctly, as the distinct votes of the…

Computer Science and Game Theory · Computer Science 2021-06-25 Zack Fitzsimmons , Edith Hemaspaandra

The voting process is formalized as a multistage voting model with successive alternative elimination. A finite number of agents vote for one of the alternatives each round subject to their preferences. If the number of votes given to the…

Optimization and Control · Mathematics 2018-08-01 Oleg A. Malafeyev , Denis Rylow , Irina Zaitseva , Anna Ermakova , Dmitry Shlaev

Inverse Reinforcement Learning (IRL) techniques deal with the problem of deducing a reward function that explains the behavior of an expert agent who is assumed to act optimally in an underlying unknown task. In several problems of…

Machine Learning · Computer Science 2024-01-09 Riccardo Poiani , Gabriele Curti , Alberto Maria Metelli , Marcello Restelli

Consider elections where the set of candidates is partitioned into parties, and each party must nominate exactly one candidate. The Possible President problem asks whether some candidate of a given party can become the winner of the…

Computer Science and Game Theory · Computer Science 2025-02-06 Ildikó Schlotter , Katarína Cechlárová

Reinforcement learning (RL) combines a control problem with statistical estimation: The system dynamics are not known to the agent, but can be learned through experience. A recent line of research casts `RL as inference' and suggests a…

Machine Learning · Computer Science 2020-11-05 Brendan O'Donoghue , Ian Osband , Catalin Ionescu

We consider a setting for Inverse Reinforcement Learning (IRL) where the learner is extended with the ability to actively select multiple environments, observing an agent's behavior on each environment. We first demonstrate that if the…

Artificial Intelligence · Computer Science 2016-01-26 Kareem Amin , Satinder Singh

In certain parliamentary democracies, there are two major parties that move in and out of power every few elections, and a third minority party that essentially never governs. We present a simple model to account for this phenomenon, in…

Physics and Society · Physics 2009-03-09 D. Volovik , M. Mobilia , S. Redner

Random Reshuffling (RR) is an algorithm for minimizing finite-sum functions that utilizes iterative gradient descent steps in conjunction with data reshuffling. Often contrasted with its sibling Stochastic Gradient Descent (SGD), RR is…

Optimization and Control · Mathematics 2021-04-06 Konstantin Mishchenko , Ahmed Khaled , Peter Richtárik

Various risk-limiting audit (RLA) methods have been developed for instant-runoff voting (IRV) elections. A recent method, AWAIRE, is the first efficient approach that can take advantage of but does not require cast vote records (CVRs).…

Computers and Society · Computer Science 2024-12-03 Alexander Ek , Philip B. Stark , Peter J. Stuckey , Damjan Vukcevic

Reinforcement learning with verifiable rewards (RLVR) is effective for training large language models on deterministic outcome reasoning tasks. Prior work shows RLVR works with few prompts, but prompt selection is often based only on…

Machine Learning · Computer Science 2026-05-07 Yujuan Pang , Jiaxin Li , Xin Sheng , Ran Peng , Yong Ma

Adaptive randomly reinforced urn (ARRU) is a two-color urn model where the updating process is defined by a sequence of non-negative random vectors $\{(D_{1,n}, D_{2,n});n\geq1\}$ and randomly evolving thresholds which utilize accruing…

Probability · Mathematics 2019-09-27 Giacomo Aletti , Andrea Ghiglietti , Anand Vidyashankar

The Single Transferable Vote (STV) is a system of preferential voting employed in multi-seat elections. Each vote cast by a voter is a (potentially partial) ranking over a set of candidates. No techniques currently exist for computing the…

Computer Science and Game Theory · Computer Science 2017-08-17 Michelle Blom , Peter J. Stuckey , Vanessa J. Teague

Recently, the educational initiative TED-Ed has published a popular brain teaser coined the 'frog riddle', which illustrates non-intuitive implications of conditional probabilities. In its intended form, the frog riddle is a reformulation…

Data Analysis, Statistics and Probability · Physics 2017-05-03 Daniel Hetterich , Florian Geissler

We consider a two-round election model involving $m$ voters and $n$ candidates. Each voter is endowed with a strict preference list ranking the candidates. In the first round, the candidates are partitioned into two subsets, $A$ and $B$,…

Computer Science and Game Theory · Computer Science 2026-03-17 Emilio De Santis , Antonio Di Crescenzo , Verdiana Mustaro
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