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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

The pairwise comparisons method is a convenient tool used when the relative order among different concepts (alternatives) needs to be determined. One popular implementation of the method is based on solving an eigenvalue problem for the…

Discrete Mathematics · Computer Science 2015-09-25 Konrad Kułakowski

Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifies a subset of input features relevant for prediction. The…

Computation and Language · Computer Science 2019-12-17 Mo Yu , Shiyu Chang , Yang Zhang , Tommi S. Jaakkola

The comparison of alternative rankings of a set of items is a general and prominent task in applied statistics. Predictor variables are ranked according to magnitude of association with an outcome, prediction models rank subjects according…

Assessing forecasting performance is a time intensive activity, often requiring months or years before we know whether or not the reported forecasts were accurate. Cognitive tests can be quickly administered and are predictive of…

Imitation learning has enabled robots to perform complex, long-horizon tasks in challenging dexterous manipulation settings. As new methods are developed, they must be rigorously evaluated and compared against corresponding baselines…

Testing the equality of two proportions is a common procedure in science, especially in medicine and public health. In these domains it is crucial to be able to quantify evidence for the absence of a treatment effect. Bayesian hypothesis…

Calibration is a classical notion from the forecasting literature which aims to address the question: how should predicted probabilities be interpreted? In a world where we only get to observe (discrete) outcomes, how should we evaluate a…

Machine Learning · Computer Science 2025-09-03 Parikshit Gopalan , Lunjia Hu

Population protocols are a relatively novel computational model in which very resource-limited anonymous agents interact in pairs with the goal of computing predicates. We consider the probabilistic version of this model, which naturally…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-09-20 Vladyslav Melnychuk

Comparative Judgement is an assessment method where item ratings are estimated based on rankings of subsets of the items. These rankings are typically pairwise, with ratings taken to be the estimated parameters from fitting a Bradley-Terry…

Methodology · Statistics 2024-05-22 Ian Hamilton , Nick Tawn

The comparison of a parameter in $k$ populations is a classical problem in statistics. Testing for the equality of means or variances are typical examples. Most procedures designed to deal with this problem assume that $k$ is fixed and that…

Mapping political party systems to metric policy spaces is one of the major methodological problems in political science. At present, in most political science project this task is performed by domain experts relying on purely qualitative…

Computation and Language · Computer Science 2023-06-06 Daria Boratyn , Damian Brzyski , Beata Kosowska-Gąstoł , Jan Rybicki , Wojciech Słomczyński , Dariusz Stolicki

Behavioural economics provides labels for patterns in human economic behaviour. Probability weighting is one such label. It expresses a mismatch between probabilities used in a formal model of a decision (i.e. model parameters) and…

Theoretical Economics · Economics 2020-05-04 Ole Peters , Alexander Adamou , Mark Kirstein , Yonatan Berman

Collaborative competitions have gained popularity in the scientific and technological fields. These competitions involve defining tasks, selecting evaluation scores, and devising result verification methods. In the standard scenario,…

Machine Learning · Computer Science 2024-08-22 Sergio Nava-Muñoz , Mario Graff , Hugo Jair Escalante

Experimental comparisons of performance represent an important aspect of research on optimization algorithms. In this work we present a methodology for defining the required sample sizes for designing experiments with desired statistical…

Neural and Evolutionary Computing · Computer Science 2018-10-16 Felipe Campelo , Fernanda Takahashi

It is common to evaluate a set of items by soliciting people to rate them. For example, universities ask students to rate the teaching quality of their instructors, and conference organizers ask authors of submissions to evaluate the…

Machine Learning · Statistics 2020-12-02 Jingyan Wang , Ivan Stelmakh , Yuting Wei , Nihar B. Shah

Comparison studies in methodological research are intended to compare methods in an evidence-based manner to help data analysts select a suitable method for their application. To provide trustworthy evidence, they must be carefully…

In this paper peer review reliability is investigated based on peer ratings of research teams at two Belgian universities. It is found that outcomes can be substantially influenced by the different ways in which experts attribute ratings.…

Digital Libraries · Computer Science 2013-07-29 Nadine Rons , Eric Spruyt

LLM-as-a-judge approaches are a practical and effective way of assessing a range of text tasks. However, when using pairwise comparisons to rank a set of candidates, the computational cost scales quadratically with the number of candidates,…

Computation and Language · Computer Science 2024-11-13 Adian Liusie , Vatsal Raina , Yassir Fathullah , Mark Gales

Statistical modeling is a powerful tool for developing and testing theories by way of causal explanation, prediction, and description. In many disciplines there is near-exclusive use of statistical modeling for causal explanation and the…

Methodology · Statistics 2011-01-06 Galit Shmueli