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Related papers: Proportional Rankings

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We propose a novel and efficient algorithm for the collaborative preference completion problem, which involves jointly estimating individualized rankings for a set of entities over a shared set of items, based on a limited number of…

Machine Learning · Statistics 2016-11-16 Suriya Gunasekar , Oluwasanmi Koyejo , Joydeep Ghosh

It is common that a jury must grade a set of candidates in a cardinal scale such as {1,2,3,4,5} or an ordinal scale such as {Great, Good, Average, Bad }. When the number of candidates is very large such as hotels (BOOKING), restaurants…

Computer Science and Game Theory · Computer Science 2023-02-24 Rida Laraki , Estelle Varloot

We study two concepts of proportionality in the model of approval-based committee elections. In degressive proportionality small minorities of voters are favored in comparison with the standard linear proportionality. Regressive…

Computer Science and Game Theory · Computer Science 2022-01-13 Michal Jaworski , Piotr Skowron

We consider three algorithms for allocating parliamentary seats by proportional representation. The usual approach to describing such algorithms is to compute a quota of votes that each party uses to "acquire'' representatives. This kind of…

Data Structures and Algorithms · Computer Science 2023-11-07 Raul Rojas

We want to select the best systems out of a given set of systems (or rank them) with respect to their expected performance. The systems allow random observations only and we assume that the joint observation of the systems has a…

Methodology · Statistics 2017-01-23 Björn Görder , Michael Kolonko

Majority voting is considered an effective method to enhance chain-of-thought reasoning, as it selects the answer with the highest "self-consistency" among different reasoning paths (Wang et al., 2023). However, previous chain-of-thought…

Computation and Language · Computer Science 2025-05-19 Weiqin Wang , Yile Wang , Hui Huang

In this paper, we consider large-scale ranking problems where one is given a set of (possibly non-redundant) pairwise comparisons and the underlying ranking explained by those comparisons is desired. We show that stochastic gradient descent…

Optimization and Control · Mathematics 2024-07-04 Benjamin Jarman , Lara Kassab , Deanna Needell , Alexander Sietsema

Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about uncertainty and multi-agent systems. When the set of agents and the set…

Computer Science and Game Theory · Computer Science 2012-07-19 Moshe Tennenholtz

Rankings are a fact of life. Whether or not one likes them, they exist and are influential. Within academia, and in computer science in particular, rankings not only capture our attention but also widely influence people who have a limited…

Ranking individuals based on their performance in different coalitions is a problem emerging in various domains (teams sports, scientific evaluation, argumentation, etc.). Often, for practical reasons, the number of comparable coalitions is…

Theoretical Economics · Economics 2026-03-19 Takahiro Suzuki , Michele Aleandri , Stefano Moretti

The proportional veto principle, which captures the idea that a candidate vetoed by a large group of voters should not be chosen, has been studied for ranked ballots in single-winner voting. We introduce a version of this principle for…

Computer Science and Game Theory · Computer Science 2025-05-05 Daniel Halpern , Ariel D. Procaccia , Warut Suksompong

We consider a social choice problem where only a small number of people out of a large population are sufficiently available or motivated to vote. A common solution to increase participation is to allow voters use a proxy, that is, transfer…

Computer Science and Game Theory · Computer Science 2016-11-28 Gal Cohensius , Shie Manor , Reshef Meir , Eli Meirom , Ariel Orda

The Probability Ranking Principle states that the document set with the highest values of probability of relevance optimizes information retrieval effectiveness given the probabilities are estimated as accurately as possible. The key point…

Information Retrieval · Computer Science 2011-08-31 Massimo Melucci

We address the critical issue of biased algorithms and unfair rankings, which have permeated various sectors, including search engines, recommendation systems, and workforce management. These biases can lead to discriminatory outcomes in a…

Computers and Society · Computer Science 2025-02-11 Chiara Criscuolo , Davide Martinenghi , Giuseppe Piccirillo

There has been great interest in fairness in machine learning, especially in relation to classification problems. In ranking-related problems, such as in online advertising, recommender systems, and HR automation, much work on fairness…

Machine Learning · Computer Science 2025-04-21 Andrii Kliachkin , Eleni Psaroudaki , Jakub Marecek , Dimitris Fotakis

Comparing the ranking of candidates by different voters is an important topic in social and information science with a high relevance from the point of view of practical applications. In general, ties and pairs of incomparable candidates…

Applications · Statistics 2016-01-25 Gergely Tibély , Péter Pollner , Gergely Palla

Algorithmic decision systems are increasingly used in areas such as hiring, school admission, or loan approval. Typically, these systems rely on labeled data for training a classification model. However, in many scenarios, ground-truth…

Machine Learning · Computer Science 2021-07-19 Jakob Schoeffer , Niklas Kuehl , Isabel Valera

In multiwinner approval voting, forming a committee that proportionally represents voters' approval ballots is an essential task. The notion of justified representation (JR) demands that any large "cohesive" group of voters should be…

Computer Science and Game Theory · Computer Science 2025-01-22 Yusuf Hakan Kalayci , Jiasen Liu , David Kempe

We consider sequential or active ranking of a set of n items based on noisy pairwise comparisons. Items are ranked according to the probability that a given item beats a randomly chosen item, and ranking refers to partitioning the items…

Machine Learning · Computer Science 2016-09-26 Reinhard Heckel , Nihar B. Shah , Kannan Ramchandran , Martin J. Wainwright

Fractional scoring has been proposed to avoid inconsistencies in the attribution of publications to percentile rank classes. Uncertainties and ambiguities in the evaluation of percentile ranks can be demonstrated most easily with small…

Digital Libraries · Computer Science 2013-03-25 Michael Schreiber
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