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We propose two solution concepts for matchings under preferences: robustness and near stability. The former strengthens while the latter relaxes the classic definition of stability by Gale and Shapley (1962). Informally speaking, robustness…

Computer Science and Game Theory · Computer Science 2019-06-06 Jiehua Chen , Piotr Skowron , Manuel Sorge

Ranking is used in sport leagues to determine a champion and/or to decide on promotion/relegation of teams. Arguably, the best known ranking method relies on scores obtained by cumulating the points associated with the wins and the draws of…

Physics and Society · Physics 2023-03-28 Leszek Szczecinski

Selective regression allows abstention from prediction if the confidence to make an accurate prediction is not sufficient. In general, by allowing a reject option, one expects the performance of a regression model to increase at the cost of…

Machine Learning · Computer Science 2022-07-18 Abhin Shah , Yuheng Bu , Joshua Ka-Wing Lee , Subhro Das , Rameswar Panda , Prasanna Sattigeri , Gregory W. Wornell

We consider the problem of ranking a set of objects based on their performance when the measurement of said performance is subject to noise. In this scenario, the performance is measured repeatedly, resulting in a range of measurements for…

Performance · Computer Science 2025-02-04 Aravind Sankaran , Lars Karlsson , Paolo Bientinesi

We study the problem of aggregating individual preferences over alternatives into a collective ranking. A distinctive feature of our setting is that agents are matched to alternatives. Applications include rankings of colleges or academic…

Theoretical Economics · Economics 2026-02-11 Gaurab Aryal , Thayer Morrill , Peter Troyan

The literature on ranking from ordinal data is vast, and there are several ways to aggregate overall preferences from pairwise comparisons between objects. In particular, it is well known that any Nash equilibrium of the zero sum game…

Machine Learning · Computer Science 2021-05-06 Kush Bhatia , Ashwin Pananjady , Peter L. Bartlett , Anca D. Dragan , Martin J. Wainwright

A new class of general exponential ranking models is introduced which we label angle-based models for ranking data. A consensus score vector is assumed, which assigns scores to a set of items, where the scores reflect a consensus view of…

Methodology · Statistics 2017-12-27 Hang Xu , Mayer Alvo , Philip L. H. Yu

In this work, we consider ranking problems among a finite set of candidates: for instance, selecting the top-$k$ items among a larger list of candidates or obtaining the full ranking of all items in the set. These problems are often…

Machine Learning · Statistics 2025-06-04 Ruiting Liang , Jake A. Soloff , Rina Foygel Barber , Rebecca Willett

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

In this paper, we address the problem of change in an abstract argumentation system. We focus on a particular change: the addition of a new argument which interacts with previous arguments. We study the impact of such an addition on the…

Artificial Intelligence · Computer Science 2014-01-17 Claudette Cayrol , Florence Dupin de Saint-Cyr , Marie-Christine Lagasquie-Schiex

We focus on the problem of ranking $N$ objects starting from a set of noisy pairwise comparisons provided by a crowd of unequal workers, each worker being characterized by a specific degree of reliability, which reflects her ability to rank…

Machine Learning · Computer Science 2023-10-04 Alessandro Nordio , Alberto tarable , Emilio Leonardi

In this paper, we study the notion of admissibility for randomised strategies in concurrent games. Intuitively, an admissible strategy is one where the player plays `as well as possible', because there is no other strategy that dominates…

Computer Science and Game Theory · Computer Science 2017-02-22 Nicolas Basset , Gilles Geeraerts , Jean-François Raskin , Ocan Sankur

Nowadays, feature selection is frequently used in machine learning when there is a risk of performance degradation due to overfitting or when computational resources are limited. During the feature selection process, the subset of features…

Machine Learning · Computer Science 2023-01-02 Sergey A. Saltykov

A fundamental principle of individual rational choice is Sen's $\gamma$ axiom, also known as expansion consistency, stating that any alternative chosen from each of two menus must be chosen from the union of the menus. Expansion consistency…

Theoretical Economics · Economics 2023-03-28 Wesley H. Holliday , Chase Norman , Eric Pacuit , Saam Zahedian

In this paper, we consider the consistency of the desirability relation with the ranking of the players in a simple game provided by some well-known solutions, in particular the Public Good Index [14] and the criticality-based ranking [1].…

Computer Science and Game Theory · Computer Science 2022-12-15 Michele Aleandri , Vito Fragnelli , Stefano Moretti

Feature selection has attracted significant attention in data mining and machine learning in the past decades. Many existing feature selection methods eliminate redundancy by measuring pairwise inter-correlation of features, whereas the…

Machine Learning · Computer Science 2015-02-03 Zhijun Chen , Chaozhong Wu , Yishi Zhang , Zhen Huang , Bin Ran , Ming Zhong , Nengchao Lyu

The axiomatic foundations of Bentham and Rawls solutions are discussed within the broader domain of cardinal preferences. It is unveiled that both solution concepts share all four of the following axioms: Nonemptiness, Anonymity, Unanimity,…

Theoretical Economics · Economics 2023-10-10 Stéphane Gonzalez , Nikolaos Pnevmatikos

Decision making is challenging when there is more than one criterion to consider. In such cases, it is common to assign a goodness score to each item as a weighted sum of its attribute values and rank them accordingly. Clearly, the ranking…

Databases · Computer Science 2018-12-20 Abolfazl Asudeh , H. V. Jagadish , Gerome Miklau , Julia Stoyanovich

The authors propose a parametric model called the arena model for prediction in paired competitions, i.e. paired comparisons with eliminations and bifurcations. The arena model has a number of appealing advantages. First, it predicts the…

Machine Learning · Computer Science 2018-11-28 Chenhe Zhang , Peiyuan Sun

This paper introduces a novel criterion, persuasiveness, to select equilibria in signaling games. In response to the Stiglitz critique, persuasiveness focuses on the comparison across equilibria. An equilibrium is more persuasive than an…

Theoretical Economics · Economics 2025-11-04 Haoyuan Zeng
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