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The rate of adoption of new information depends on reinforcement from multiple sources in a way that often cannot be described by simple contagion processes. In such cases, contagion is said to be complex. Complex contagion happens in the…

Physics and Society · Physics 2019-06-21 Vítor V. Vasconcelos , Simon A. Levin , Flávio L. Pinheiro

We study a distributed learning process observed in human groups and other social animals. This learning process appears in settings in which each individual in a group is trying to decide over time, in a distributed manner, which option to…

Machine Learning · Computer Science 2017-05-10 L. Elisa Celis , Peter M. Krafft , Nisheeth K. Vishnoi

Current practice for evaluating recommender systems typically focuses on point estimates of user-oriented effectiveness metrics or business metrics, sometimes combined with additional metrics for considerations such as diversity and…

Information Retrieval · Computer Science 2023-09-13 Michael D. Ekstrand , Ben Carterette , Fernando Diaz

We characterize the identified sets of a wide range of stochastic choice models, including random utility, various models of boundedly-rational behavior, and dynamic discrete choice. In each of these settings, we show two distributions over…

Theoretical Economics · Economics 2026-02-24 Peter Caradonna , Christopher Turansick

Statistical thinking partially depends upon an iterative process by which essential features of a problem setting are identified and mapped onto an abstract model or archetype, and then translated back into the context of the original…

Other Statistics · Statistics 2019-02-21 Matthew Beckman , Robert delMas

Understanding the importance of the inputs on the output is useful across many tasks. This work provides an information-theoretic framework to analyse the influence of inputs for text classification tasks. Natural language processing (NLP)…

Computation and Language · Computer Science 2024-02-05 Luran Wang , Mark Gales , Vatsal Raina

I study partial identification of distributional parameters in triangular systems. This model consists of a nonparametric outcome equation and a selection equation. This allows for general unobserved heterogeneity and selection on…

Methodology · Statistics 2014-11-11 Ju Hyun Kim

Model-based approaches bear great promise for decision making of agents interacting with the physical world. In the context of spatial environments, different types of problems such as localisation, mapping, navigation or autonomous…

Machine Learning · Statistics 2019-06-21 Atanas Mirchev , Baris Kayalibay , Maximilian Soelch , Patrick van der Smagt , Justin Bayer

Selection bias arises when the probability that an observation enters a dataset depends on variables related to the quantities of interest, leading to systematic distortions in estimation and uncertainty quantification. For example, in…

Most decisions require information gathering from a stimulus presented with different gaps. Indeed, the brain process of this integration is rarely ambiguous. Recently, it has been claimed that humans can optimally integrate the information…

Neurons and Cognition · Quantitative Biology 2018-10-29 Maryam Tohidi-Moghaddam , Sajjad Zabbah , Farzaneh Olianezhad , Reza Ebrahimpour

Sequential sampling occurs when the entire population is not known in advance and data are obtained one at a time or in groups of units. This manuscript proposes a new algorithm to sequentially select a balanced sample. The algorithm…

Methodology · Statistics 2023-01-04 Raphaël Jauslin , Bardia Panahbehagh , Yves Tillé

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are…

Populations and Evolution · Quantitative Biology 2018-07-19 George W. A. Constable , Alan J. McKane

Standard methods for aligning large language models with human preferences learn from pairwise comparisons among sampled candidate responses and regularize toward a reference policy. Despite their effectiveness, the effects of sampling and…

Machine Learning · Computer Science 2026-02-13 Yurong Chen , Yu He , Michael I. Jordan , Fan Yao

The objective of this paper is to give a rigorous analysis of a stochastic spatial model of producer-consumer systems that has been recently introduced by Kang and the author to understand the role of space in ecological communities in…

Probability · Mathematics 2013-01-03 Nicolas Lanchier

A spatial point process can be characterized by an intensity function which predicts the number of events that occur across space. In this paper, we develop a method to infer predictive intensity intervals by learning a spatial model using…

Machine Learning · Statistics 2020-07-06 Muhammad Osama , Dave Zachariah , Petre Stoica

We consider the stochastic ranking process with space-time dependent jump rates for the particles. The process is a simplified model of the time evolution of the rankings such as sales ranks at online bookstores. We prove that the joint…

Probability · Mathematics 2013-01-01 Tetsuya Hattori , Seiichiro Kusuoka

We tackle the problem of conditioning probabilistic programs on distributions of observable variables. Probabilistic programs are usually conditioned on samples from the joint data distribution, which we refer to as deterministic…

Machine Learning · Computer Science 2021-03-09 David Tolpin , Yuan Zhou , Tom Rainforth , Hongseok Yang

The outcomes of elections, product sales, and the structure of social connections are all determined by the choices individuals make when presented with a set of options, so understanding the factors that contribute to choice is crucial. Of…

Machine Learning · Computer Science 2020-11-09 Kiran Tomlinson , Austin R. Benson

In this paper, we investigate the role of uninformed individuals in consensus formation within opinion-swarming models for self-propelled particles. The proposed models are inspired by empirical observations in animal swarming, particularly…

Physics and Society · Physics 2025-08-12 Gissell Estrada-Rodriguez , Victor Villegas-Morral , Marie-Therese Wolfram

A case is made that researchers are interested in studying processes. Often the inferences they are interested in making are about the process and its associated population. On other occasions, a researcher may be interested in making an…

Other Statistics · Statistics 2022-06-20 Charles W. Champ , Andrew V. Sills