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Determining a winner among a set of items using active pairwise comparisons under a limited budget is a challenging problem in preference-based learning. The goal of this study is to implement and evaluate the PARWiS algorithm, which shows…

Machine Learning · Computer Science 2026-03-03 Shailendra Bhandari

The paper deals with the problem of finding the best alternatives on the basis of pairwise comparisons when these comparisons need not be transitive. In this setting, we study a reinforcement urn model. We prove convergence to the optimal…

Optimization and Control · Mathematics 2013-01-25 Benoit Laslier , Jean-Francois Laslier

The paper reviews some axioms of additivity concerning ranking methods used for generalized tournaments with possible missing values and multiple comparisons. It is shown that one of the most natural properties, called consistency, has…

Computer Science and Game Theory · Computer Science 2015-12-02 László Csató

Round robin tournaments are omnipresent in sport competitions and beyond. We propose two new integer programming formulations for scheduling a round robin tournament, one of which we call the matching formulation. We analytically compare…

Optimization and Control · Mathematics 2022-10-18 Jasper van Doornmalen , Christopher Hojny , Roel Lambers , Frits C. R. Spieksma

Pairwise comparison matrices are widely used in Multicriteria Decision Making. This article applies incomplete pairwise comparison matrices in the area of sport tournaments, namely proposing alternative rankings for the 2010 Chess Olympiad…

Applications · Statistics 2019-06-20 László Csató

We examine three methods for ranking by pairwise comparison: Principal Eigenvector, HodgeRank and Tropical Eigenvector. It is shown that the choice of method can produce arbitrarily different rank order.To be precise, for any two of the…

Methodology · Statistics 2011-03-08 Ngoc Mai Tran

Ranking objects is a simple and natural procedure for organizing data. It is often performed by assigning a quality score to each object according to its relevance to the problem at hand. Ranking is widely used for object selection, when…

Artificial Intelligence · Computer Science 2012-06-26 Or Zuk , Liat Ein-Dor , Eytan Domany

Recommender systems are one of the most pervasive applications of machine learning in industry, with many services using them to match users to products or information. As such it is important to ask: what are the possible fairness risks,…

Computers and Society · Computer Science 2019-03-12 Alex Beutel , Jilin Chen , Tulsee Doshi , Hai Qian , Li Wei , Yi Wu , Lukasz Heldt , Zhe Zhao , Lichan Hong , Ed H. Chi , Cristos Goodrow

We study very simple sorting algorithms based on a probabilistic comparator model. In our model, errors in comparing two elements are due to (1) the energy or effort put in the comparison and (2) the difference between the compared…

Data Structures and Algorithms · Computer Science 2018-05-16 Barbara Geissmann , Paolo Penna

In a round-robin tournament, a team may lack the incentive to win if its final rank does not depend on the outcome of the matches still to be played. This paper introduces a classification scheme to determine these weakly (where one team is…

Optimization and Control · Mathematics 2024-01-26 László Csató , Roland Molontay , József Pintér

Tournament solutions are frequently used to select winners from a set of alternatives based on pairwise comparisons between alternatives. Prior work has shown that several common tournament solutions tend to select large winner sets and…

Computer Science and Game Theory · Computer Science 2021-09-30 Markus Brill , Ulrike Schmidt-Kraepelin , Warut Suksompong

This paper proposes a new method for solving the well-known rank aggregation problem from pairwise comparisons using the method of low-rank matrix completion. The partial and noisy data of pairwise comparisons is transformed into a matrix…

Machine Learning · Statistics 2018-06-15 Tal Levy , Alireza Vahid , Raja Giryes

Algorithms which sort lists of real numbers into ascending order have been studied for decades. They are typically based on a series of pairwise comparisons and run entirely on chip. However people routinely sort lists which depend on…

Artificial Intelligence · Computer Science 2016-12-28 Samuel L Smith

Given a number of pairwise preferences of items, a common task is to rank all the items. Examples include pairwise movie ratings, New Yorker cartoon caption contests, and many other consumer preferences tasks. What these settings have in…

Machine Learning · Computer Science 2020-07-06 Umang Varma , Lalit Jain , Anna C. Gilbert

Fair ranking problems arise in many decision-making processes that often necessitate a trade-off between accuracy and fairness. Many existing studies have proposed correction methods such as adding fairness constraints to a ranking model's…

Machine Learning · Computer Science 2022-04-26 Ryosuke Sonoda

There is a growing body of work on sorting and selection in models other than the unit-cost comparison model. This work is the first treatment of a natural stochastic variant of the problem where the cost of comparing two elements is a…

Data Structures and Algorithms · Computer Science 2007-10-02 Stanislav Angelov , Keshav Kunal , Andrew McGregor

The area of computing with uncertainty considers problems where some information about the input elements is uncertain, but can be obtained using queries. For example, instead of the weight of an element, we may be given an interval that is…

Data Structures and Algorithms · Computer Science 2021-01-15 Thomas Erlebach , Michael Hoffmann , Murilo S. de Lima

In this paper we bring a novel approach to the theory of tournament rankings. We combine two different theories that are widely used to establish rankings of populations after a given tournament. First, we use the statistical approach of…

General Mathematics · Mathematics 2007-05-23 M. Brozos-Vazquez , M. A. Campo-Cabana , J. C. Diaz-Ramos , J. Gonzalez-Diaz

We address the problem of learning a ranking by using adaptively chosen pairwise comparisons. Our goal is to recover the ranking accurately but to sample the comparisons sparingly. If all comparison outcomes are consistent with the ranking,…

Machine Learning · Statistics 2017-06-16 Lucas Maystre , Matthias Grossglauser

A principled approach to cyclicality and intransitivity in paired comparison data is developed. The proposed methodology enables more precise estimation of the underlying preference profile and facilitates the identification of all cyclic…

Methodology · Statistics 2025-10-08 Rahul Singh , Ori Davidov