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It is common to be interested in rankings or order relationships among entities. In complex settings where one does not directly measure a univariate statistic upon which to base ranks, such inferences typically rely on statistical models…

Methodology · Statistics 2022-04-12 Andres F. Barrientos , Deborshee Sen , Garritt L Page , David B Dunson

Pairwise ranking systems based on Maximum Likelihood Estimation (MLE), such as the Bradley-Terry model, are widely used to aggregate preferences from pairwise comparisons. However, their robustness under strategic data manipulation remains…

Machine Learning · Computer Science 2026-04-21 Junyi Yao , Zihao Zheng , Jiayu Long

We attack the problem of getting a strict ranking (i.e. a ranking without equally ranked items) of $n$ items from a pairwise comparisons matrix. Basic structures are described, a first heuristical approach based on a condition, the…

Information Theory · Computer Science 2026-04-14 Jean-Pierre Magnot

Learning to rank is an effective recommendation approach since its introduction around 2010. Famous algorithms such as Bayesian Personalized Ranking and Collaborative Less is More Filtering have left deep impact in both academia and…

Information Retrieval · Computer Science 2022-12-21 Hao Wang

Over the last few years, there has been a growing interest in the prediction and modelling of competitive sports outcomes, with particular emphasis placed on this area by the Bayesian statistics and machine learning communities. In this…

Applications · Statistics 2024-12-17 Roberto Macrì Demartino , Leonardo Egidi , Nicola Torelli

Using theory and experiments, this paper shows that the difficulty of making tradeoffs offers a parsimonious explanation for a wide range of behavioral phenomena. We develop a model of imprecise comparisons applicable to multiattribute,…

General Economics · Economics 2026-04-01 Cassidy Shubatt , Jeffrey Yang

We propose a topic modeling approach to the prediction of preferences in pairwise comparisons. We develop a new generative model for pairwise comparisons that accounts for multiple shared latent rankings that are prevalent in a population…

Machine Learning · Computer Science 2015-01-27 Weicong Ding , Prakash Ishwar , Venkatesh Saligrama

Analogical reasoning depends fundamentally on the ability to learn and generalize about relations between objects. We develop an approach to relational learning which, given a set of pairs of objects…

Methodology · Statistics 2013-08-30 Ricardo Silva , Katherine Heller , Zoubin Ghahramani , Edoardo M. Airoldi

Many statistical experiments involve comparing multiple population groups. For example, a public opinion poll may ask which of several political candidates commands the most support; a social scientific survey may report the most common of…

Methodology · Statistics 2019-03-20 Kenneth Hung , William Fithian

This paper proposes a model to explain the potential role of inter-group conflicts in determining the rise and fall of signaling norms. Individuals in a population are characterized by high and low productivity types and they are matched in…

Populations and Evolution · Quantitative Biology 2023-08-08 Ethan Holdahl , Jiabin Wu

Members of a social species need to make appropriate decisions about who, how, and when to interact with others in their group. However, it has been difficult for researchers to detect the inputs to these decisions and, in particular, how…

Populations and Evolution · Quantitative Biology 2024-07-15 Elizabeth A. Hobson , Dan Mønster , Simon DeDeo

We consider the predictive problem of supervised ranking, where the task is to rank sets of candidate items returned in response to queries. Although there exist statistical procedures that come with guarantees of consistency in this…

Statistics Theory · Mathematics 2013-11-27 John C. Duchi , Lester Mackey , Michael I. Jordan

The problem of ranking is a multi-billion dollar problem. In this paper we present an overview of several production quality ranking systems. We show that due to conflicting goals of employing the most effective machine learning models and…

Information Retrieval · Computer Science 2019-07-30 Murium Iqbal , Nishan Subedi , Kamelia Aryafar

Modern Reinforcement Learning (RL) algorithms are able to outperform humans in a wide variety of tasks. Multi-agent reinforcement learning (MARL) settings present additional challenges, and successful cooperation in mixed-motive groups of…

Multiagent Systems · Computer Science 2024-06-25 Ram Rachum , Yonatan Nakar , Bill Tomlinson , Nitay Alon , Reuth Mirsky

One of the most crucial issues in data mining is to model human behaviour in order to provide personalisation, adaptation and recommendation. This usually involves implicit or explicit knowledge, either by observing user interactions, or by…

Human-Computer Interaction · Computer Science 2017-08-21 Kevin Jasberg , Sergej Sizov

This paper tackles the critical challenge of human-AI complementarity in decision-making. Departing from the traditional focus on algorithmic performance in favor of performance of the human-AI team, and moving past the framing of…

Artificial Intelligence · Computer Science 2025-11-04 Ruijiang Gao , Maytal Saar-Tsechansky , Maria De-Arteaga

We present ten different strength-based statistical models that we use to model soccer match outcomes with the aim of producing a new ranking. The models are of four main types: Thurstone-Mosteller, Bradley-Terry, Independent Poisson and…

Applications · Statistics 2018-11-15 Christophe Ley , Tom Van de Wiele , Hans Van Eetvelde

Ranking of agents competing with each other in complex systems may lead to paradoxes according to the pre-chosen different measures. A discussion is presented on such rank-rank, similar or not, correlations based on the case of European…

Physics and Society · Physics 2014-10-20 Marcel Ausloos , Rudi Cloots , Adam Gadomski , Nikolay K. Vitanov

Most decision-making models, including the pairwise comparison method, assume the decision-makers honesty. However, it is easy to imagine a situation where a decision-maker tries to manipulate the ranking results. This paper presents three…

Artificial Intelligence · Computer Science 2024-10-11 Michał Strada , Sebastian Ernst , Jacek Szybowski , Konrad Kułakowski

Rank aggregation with pairwise comparisons is widely encountered in sociology, politics, economics, psychology, sports, etc . Given the enormous social impact and the consequent incentives, the potential adversary has a strong motivation to…

Artificial Intelligence · Computer Science 2024-07-03 Ke Ma , Qianqian Xu , Jinshan Zeng , Wei Liu , Xiaochun Cao , Yingfei Sun , Qingming Huang
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