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In several decision-making problems, alternatives should be ranked on the basis of paired comparisons between them. We present an axiomatic approach for the universal ranking problem with arbitrary preference intensities, incomplete and…

Computer Science and Game Theory · Computer Science 2019-04-10 László Csató

Semi-supervised and unsupervised machine learning methods often rely on graphs to model data, prompting research on how theoretical properties of operators on graphs are leveraged in learning problems. While most of the existing literature…

Analysis of PDEs · Mathematics 2021-01-12 Amber Yuan , Jeff Calder , Braxton Osting

A deformation of the combinatorial Laplacian is proposed, consisting in a generalization of several existing Laplacians. As particular cases of this construction, the dilation Laplacians are shown to be useful tools for ranking in directed…

Physics and Society · Physics 2017-10-25 Michaël Fanuel , Johan A. K. Suykens

Object ranking or "learning to rank" is an important problem in the realm of preference learning. On the basis of training data in the form of a set of rankings of objects represented as feature vectors, the goal is to learn a ranking…

Machine Learning · Statistics 2017-12-05 Mohsen Ahmadi Fahandar , Eyke Hüllermeier

Understanding the correlation between two different scores for the same set of items is a common problem in information retrieval, and the most commonly used statistics that quantifies this correlation is Kendall's $\tau$. However, the…

Social and Information Networks · Computer Science 2014-11-03 Sebastiano Vigna

We study ranked enumeration for Conjunctive Queries (CQs) where the answers are ordered by a given ranking function (e.g., an ORDER BY clause in SQL). We develop "any-k" algorithms, which, without knowing the number k of desired answers,…

Databases · Computer Science 2023-10-16 Nikolaos Tziavelis , Wolfgang Gatterbauer , Mirek Riedewald

Reasoning about agent preferences on a set of alternatives, and the aggregation of such preferences into some social ranking is a fundamental issue in reasoning about uncertainty and multi-agent systems. When the set of agents and the set…

Computer Science and Game Theory · Computer Science 2012-07-19 Moshe Tennenholtz

This paper develops a theory of competitive equilibrium with indivisible goods based entirely on economic conditions on demand. The key idea is to analyze complementarity and substitutability between bundles of goods, rather than merely…

Theoretical Economics · Economics 2024-12-12 Ravi Jagadeesan , Alexander Teytelboym

Rank aggregation aims to combine the preference rankings of a number of alternatives from different voters into a single consensus ranking. As a useful model for a variety of practical applications, however, it is a computationally…

Neural and Evolutionary Computing · Computer Science 2022-01-12 Yangming Zhou , Jin-Kao Hao , Zhen Li , Fred Glover

Ranking systems are ubiquitous in modern Internet services, including online marketplaces, social media, and search engines. Traditionally, ranking systems only focus on how to get better relevance estimation. When relevance estimation is…

Information Retrieval · Computer Science 2022-12-20 Tao Yang , Zhichao Xu , Zhenduo Wang , Anh Tran , Qingyao Ai

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

In this paper we analyze the PageRank of a complex network as a function of its personalization vector. By using this approach, a complete characterization of the existence and uniqueness of fixed points of PageRank of a graph is given in…

Social and Information Networks · Computer Science 2025-07-28 David Aleja , Julio Flores , Eva Primo , Daniel Rodríguez , Miguel Romance

Conventional Learning-to-Rank (LTR) methods optimize the utility of the rankings to the users, but they are oblivious to their impact on the ranked items. However, there has been a growing understanding that the latter is important to…

Machine Learning · Computer Science 2019-06-28 Ashudeep Singh , Thorsten Joachims

In the paper we compare well known numerical methods of finding PageRank vector. We propose Markov Chain Monte Carlo method and obtain a new estimation for this method. We also propose a new method for PageRank problem based on the…

Optimization and Control · Mathematics 2016-05-27 Alexander Gasnikov , Denis Dmitriev

In the algorithm Intersort, Chevalley et al. (2024) proposed a score-based method to discover the causal order of variables in a Directed Acyclic Graph (DAG) model, leveraging interventional data to outperform existing methods. However, as…

Machine Learning · Computer Science 2024-10-14 Mathieu Chevalley , Arash Mehrjou , Patrick Schwab

This paper studies human preference learning based on partially revealed choice behavior and formulates the problem as a generalized Bradley-Terry-Luce (BTL) ranking model that accounts for heterogeneous preferences. Specifically, we assume…

Methodology · Statistics 2025-09-03 Jianqing Fan , Hyukjun Kwon , Xiaonan Zhu

The study of IR evaluation metrics through axiomatic analysis enables a better understanding of their numerical properties. Some works have modelled the effectiveness of retrieval metrics with axioms that capture desirable properties on the…

Information Retrieval · Computer Science 2022-07-05 Fernando Giner

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

We consider the problem of allocating indivisible goods in a way that is fair, using one of the leading market mechanisms in economics: the competitive equilibrium from equal incomes. Focusing on two major classes of valuations, namely…

Computer Science and Game Theory · Computer Science 2016-07-19 Simina Brânzei , Hadi Hosseini , Peter Bro Miltersen

In this paper we present a new method that can accelerate the computation of the PageRank importance vector. Our method, called D-Iteration (DI), is based on the decomposition of the matrix-vector product that can be seen as a fluid…

Data Structures and Algorithms · Computer Science 2015-05-07 Dohy Hong , The Dang Huynh , Fabien Mathieu