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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

This paper considers ranking inference of $n$ items based on the observed data on the top choice among $M$ randomly selected items at each trial. This is a useful modification of the Plackett-Luce model for $M$-way ranking with only the top…

Methodology · Statistics 2023-01-09 Jianqing Fan , Zhipeng Lou , Weichen Wang , Mengxin Yu

Statistical inference in parametric models (e.g., the Bradley--Terry model and its variants) for paired-comparison data has been explored in the high-dimensional regime, in which the number of items involving in paired comparisons diverges.…

Methodology · Statistics 2026-04-01 Haoyue Song , Lianqiang Qu , Ting Yan , Yuguo Chen

There is a common belief that humans and many animals follow transitive inference (choosing A over C on the basis of knowing that A is better than B and B is better than C). Transitivity seems to be the essence of rational choice. We…

Computer Science and Game Theory · Computer Science 2014-09-23 Marcin Makowski , Edward W. Piotrowski

We study social choice mechanisms in an implicit utilitarian framework with a metric constraint, where the goal is to minimize \textit{Distortion}, the worst case social cost of an ordinal mechanism relative to underlying cardinal…

Computer Science and Game Theory · Computer Science 2020-07-03 Brandon Fain , Ashish Goel , Kamesh Munagala , Nina Prabhu

Collaborative filtering is the process of making recommendations regarding the potential preference of a user, for example shopping on the Internet, based on the preference ratings of the user and a number of other users for various items.…

Information Retrieval · Computer Science 2013-01-14 Rita Sharma , David L Poole

Arrow's Theorem concerns a fundamental problem in social choice theory: given the individual preferences of members of a group, how can they be aggregated to form rational group preferences? Arrow showed that in an election between three or…

Probability · Mathematics 2021-09-27 Frederic Koehler , Elchanan Mossel

Variable selection, also known as feature selection in machine learning, plays an important role in modeling high dimensional data and is key to data-driven scientific discoveries. We consider here the problem of detecting influential…

Methodology · Statistics 2014-09-24 Bo Jiang , Jun S. Liu

Considering voting rules based on evaluation inputs rather than preference rankings modifies the paradigm of probabilistic studies of voting procedures. This article proposes several simulation models for generating evaluation-based voting…

Applications · Statistics 2024-03-18 Antoine Rolland , Jean-Baptiste Aubin , Irène Gannaz , Samuela Leoni

Despite extensive theoretical research on proportionality in approval-based multiwinner voting, its impact on which committees and candidates can be selected in practice remains poorly understood. We address this gap by (i) analyzing the…

Computer Science and Game Theory · Computer Science 2025-11-13 Niclas Boehmer , Lara Glessen , Jannik Peters

This paper discusses {General Random Utility Models (GRUMs)}. These are a class of parametric models that generate partial ranks over alternatives given attributes of agents and alternatives. We propose two preference elicitation scheme for…

Artificial Intelligence · Computer Science 2013-09-27 Hossein Azari Soufiani , David C. Parkes , Lirong Xia

Given a set of pairwise comparisons, the classical ranking problem computes a single ranking that best represents the preferences of all users. In this paper, we study the problem of inferring individual preferences, arising in the context…

Machine Learning · Statistics 2015-12-18 Rui Wu , Jiaming Xu , R. Srikant , Laurent Massoulié , Marc Lelarge , Bruce Hajek

Ranking problems based on pairwise comparisons, such as those arising in online gaming, often involve a large pool of items to order. In these situations, the gap in performance between any two items can be significant, and the smallest and…

Statistics Theory · Mathematics 2022-06-16 Heejong Bong , Alessandro Rinaldo

We focus on the majority model in a topology consisting of two coupled fully-connected networks, thereby mimicking the existence of communities in social networks. We show that a transition takes place at a value of the inter-connectivity…

Physics and Society · Physics 2007-06-13 R. Lambiotte , M. Ausloos , J. Holyst

Generally speaking, the model training for recommender systems can be based on two types of data, namely explicit feedback and implicit feedback. Moreover, because of its general availability, we see wide adoption of implicit feedback data,…

Information Retrieval · Computer Science 2023-04-17 Yi Ren , Hongyan Tang , Jiangpeng Rong , Siwen Zhu

In repeated-game applications where both the collusive and non-collusive outcomes can be supported as equilibria, researchers must resolve underlying selection questions if theory will be used to understand counterfactual policies. One…

General Economics · Economics 2021-01-18 Emanuel Vespa , Taylor Weidman , Alistair J. Wilson

This study presents a semi-nonparametric Latent Class Choice Model (LCCM) with a flexible class membership component. The proposed model formulates the latent classes using mixture models as an alternative approach to the traditional random…

The voter model is a classical interacting particle system, modelling how global consensus is formed by local imitation. We analyse the time to consensus for a particular family of voter models when the underlying structure is a scale-free…

Probability · Mathematics 2024-01-11 John Fernley

Rankings derived from pairwise comparisons are central to many economic and computational systems. In the context of large language models (LLMs), rankings are typically constructed from human preference data and presented as leaderboards…

Computation and Language · Computer Science 2026-03-05 Angel Rodrigo Avelar Menendez , Yufeng Liu , Xiaowu Dai

In this paper, we study the linear transformation model in the most general setup. This model includes many important and popular models in statistics and econometrics as special cases. Although it has been studied for many years, the…

Methodology · Statistics 2021-03-26 Tao Yu , Pengfei Li , Baojiang Chen , Ao Yuan , Jing Qin
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