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Related papers: A continuous rating method for preferential voting

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Recommender systems can be formulated as a matrix completion problem, predicting ratings from user and item parameter vectors. Optimizing these parameters by subsampling data becomes difficult as the number of users and items grows. We…

Information Retrieval · Computer Science 2018-07-09 Elias Tragas , Calvin Luo , Maxime Gazeau , Kevin Luk , David Duvenaud

With ever-increasing available data, predicting individuals' preferences and helping them locate the most relevant information has become a pressing need. Understanding and predicting preferences is also important from a fundamental point…

Physics and Society · Physics 2012-10-05 Roger Guimera , Alejandro Llorente , Esteban Moro , Marta Sales-Pardo

Not long ago primary census data became available to publicity. It opened qualitatively new perspectives not only for researchers in demography and sociology, but also for those people, who somehow face processes occurring in society. In…

Databases · Computer Science 2011-06-28 Oleg Chertov , Marharyta Aleksandrova

Large deviations for additive path functionals of stochastic processes have attracted significant research interest, in particular in the context of stochastic particle systems and statistical physics. Efficient numerical `cloning'…

Probability · Mathematics 2021-07-21 Letizia Angeli , Stefan Grosskinsky , Adam M. Johansen

Model selection is a major challenge in non-parametric clustering. There is no universally admitted way to evaluate clustering results for the obvious reason that no ground truth is available. The difficulty to find a universal evaluation…

Machine Learning · Computer Science 2023-05-18 Alex Mourer , Florent Forest , Mustapha Lebbah , Hanane Azzag , Jérôme Lacaille

In this paper, we advocate a novel measure for the purpose of checking the quality of a cluster partition for a sample into several distinct classes, and thus, determine the unknown value for the true number of clusters prevailing the…

Applications · Statistics 2024-04-12 Soumita Modak

Clustering is a usual unsupervised machine learning technique for grouping the data points into groups based upon similar features. We focus here on unsupervised clustering for contaminated data, i.e in the case where K-medians should be…

Statistics Theory · Mathematics 2024-02-28 Antoine Godichon-Baggioni , Sobihan Surendran

The paper surveys more than forty characterizations of scoring methods for preference aggregation and contains one new result. A general scoring operator is {\it self-consistent} if alternative $i$ is assigned a greater score than $j$…

Optimization and Control · Mathematics 2007-05-23 Pavel Chebotarev , Elena Shamis

Understanding user preference is essential to the optimization of recommender systems. As a feedback of user's taste, rating scores can directly reflect the preference of a given user to a given product. Uncovering the latent components of…

Information Retrieval · Computer Science 2017-10-20 Junhua Chen , Wei Zeng , Junming Shao , Ge Fan

The ability to measure the satisfaction of (groups of) voters is a crucial prerequisite for formulating proportionality axioms in approval-based participatory budgeting elections. Two common - but very different - ways to measure the…

Computer Science and Game Theory · Computer Science 2023-10-19 Markus Brill , Stefan Forster , Martin Lackner , Jan Maly , Jannik Peters

Cluster randomized trials are widely used when individual randomization is logistically infeasible or when correlations between observations cannot be ignored, especially in fields such as ophthalmology, infectious disease, vaccine…

Methodology · Statistics 2026-05-04 Wanying Shao , Toshimitsu Hamasaki , Scott Evans , Guoqing Diao

The selection of the best classification algorithm for a given dataset is a very widespread problem. It is also a complex one, in the sense it requires to make several important methodological choices. Among them, in this work we focus on…

Machine Learning · Computer Science 2012-07-18 Vincent Labatut , Hocine Cherifi

The standard way to evaluate language models on subjective tasks is through pairwise comparisons: an annotator chooses the "better" of two responses to a prompt. Leaderboards aggregate these comparisons into a single Bradley-Terry (BT)…

Machine Learning · Computer Science 2026-02-26 Hadi Khalaf , Serena L. Wang , Daniel Halpern , Itai Shapira , Flavio du Pin Calmon , Ariel D. Procaccia

Feature selection can facilitate the learning of mixtures of discrete random variables as they arise, e.g. in crowdsourcing tasks. Intuitively, not all workers are equally reliable but, if the less reliable ones could be eliminated, then…

Machine Learning · Statistics 2017-11-28 Vincent Zhao , Steven W. Zucker

The quantile admission process with veto power is a stochastic processes suggested by Alon, Feldman, Mansour, Oren and Tennenholtz as a model for the evolution of an exclusive social group. The model itself consists of a growing multiset of…

Probability · Mathematics 2018-07-17 Naomi Feldheim , Ohad Noy Feldheim

We analyse a preferential urn model with randomness using the replica method. The preferential urn model is a stochastic model based on the concept "the rich get richer." The replica analysis clarifies that the preferential urn model with…

Disordered Systems and Neural Networks · Physics 2009-11-11 Jun Ohkubo , Muneki Yasuda , Kazuyuki Tanaka

The statistical properties of pairwise majority voting over S alternatives is analyzed in an infinite random population. We first compute the probability that the majority is transitive (i.e. that if it prefers A to B to C, then it prefers…

Statistical Mechanics · Physics 2009-11-10 Giacomo Raffaelli , Matteo Marsili

Schulze voting is a recently introduced voting system enjoying unusual popularity and a high degree of real-world use, with users including the Wikimedia foundation, several branches of the Pirate Party, and MTV. It is a Condorcet voting…

Computer Science and Game Theory · Computer Science 2013-05-27 Curtis Menton , Preetjot Singh

Given a large population, it is an intensive task to gather individual preferences over a set of alternatives and arrive at an aggregate or collective preference of the population. We show that social network underlying the population can…

Social and Information Networks · Computer Science 2017-11-17 Swapnil Dhamal , Rohith D. Vallam , Y. Narahari

Feature selection is a vital technique in machine learning, as it can reduce computational complexity, improve model performance, and mitigate the risk of overfitting. However, the increasing complexity and dimensionality of datasets pose…

Machine Learning · Computer Science 2024-07-24 Yuepeng Chen , Weiping Ding , Hengrong Ju , Jiashuang Huang , Tao Yin