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Multivariate count data are defined as the number of items of different categories issued from sampling within a population, which individuals are grouped into categories. The analysis of multivariate count data is a recurrent and crucial…

Machine Learning · Statistics 2013-12-17 Pierre Fernique , Jean-Baptiste Durand , Yann Guédon

This paper develops some mathematical models arising in behavioral sciences, particularly in psychology, which are formalized via general preferences with variable ordering structures. Our considerations are based on the recent variational…

Optimization and Control · Mathematics 2013-11-26 T. Q. Bao , B. S. Mordukhovich , A. Soubeyran

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

Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat other domain attributes: as a random variable with a density…

Artificial Intelligence · Computer Science 2013-01-18 Urszula Chajewska , Daphne Koller

The equations of evolutionary change by natural selection are commonly expressed in statistical terms. Fisher's fundamental theorem emphasizes the variance in fitness. Quantitative genetics expresses selection with covariances and…

Populations and Evolution · Quantitative Biology 2012-11-20 Steven A. Frank

Productions functions map the inputs of a firm or a productive system onto its outputs. This article expounds generalizations of the production function that include state variables, organizational structures and increasing returns to…

Physics and Society · Physics 2008-12-02 Guido Fioretti

Observed clusters should be modelled by considering the distribution function to be a random variable that quantifies the degree of excitation of the system's normal modes. A system of canonical coordinates for the space of DFs is…

Astrophysics of Galaxies · Physics 2021-08-11 Jun Yan Lau , James Binney

Diffusion models are a class of probabilistic generative models that have been widely used as a prior for image processing tasks like text conditional generation and inpainting. We demonstrate that these models can be adapted to make…

Machine Learning · Computer Science 2023-06-14 Marc Finzi , Anudhyan Boral , Andrew Gordon Wilson , Fei Sha , Leonardo Zepeda-Núñez

How do we know that a kitchen is a kitchen by looking? Relatively little is known about how we conceptualize and categorize different visual environments. Traditional models of visual perception posit that scene categorization is achieved…

Neurons and Cognition · Quantitative Biology 2014-11-20 Michelle R. Greene , Christopher Baldassano , Andre Esteva , Diane M. Beck , Li Fei-Fei

The problem of quantification of emotions in the choice between alternatives is considered. The alternatives are evaluated in a dual manner. From one side, they are characterized by rational features defining the utility of each…

Artificial Intelligence · Computer Science 2022-03-07 V. I. Yukalov

Geometric quantiles are popular location functionals to build rank-based statistical procedures in multivariate settings. They are obtained through the minimization of a non-smooth convex objective function. As a result, the singularity of…

Statistics Theory · Mathematics 2026-02-11 Dimitri Konen , Gilles Stupfler

Physics is based on probabilities as fundamental entities of a mathematical description. Expectation values of observables are computed according to the classical statistical rule. The overall probability distribution for one world covers…

Quantum Physics · Physics 2024-10-28 C. Wetterich

Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that appear in imprecise-probabilistic decision…

Artificial Intelligence · Computer Science 2019-05-22 Jasper De Bock , Gert de Cooman

The diffusion probabilistic generative models are widely used to generate high-quality data. Though they can synthetic data that does not exist in the training set, the rationale behind such generalization is still unexplored. In this…

Machine Learning · Computer Science 2023-05-25 Mingyang Yi , Jiacheng Sun , Zhenguo Li

In physics we often use very simple models to describe systems with many degrees of freedom, but it is not clear why or how this success can be transferred to the more complex biological context. We consider models for the joint…

Neurons and Cognition · Quantitative Biology 2024-12-06 Luisa Ramirez , William Bialek , Stephanie E. Palmer , David J. Schwab

Choice consistency with utility maximization, as a key assumption in economics, has been extensively used to evaluate decision quality of individuals and to predict real-world outcomes across different contexts. Here we investigate the…

General Economics · Economics 2025-09-22 Mingshi Chen , Tracy Xiao Liu , You Shan , Shu Wang , Songfa Zhong , Yanju Zhou

Experimental neuroscience increasingly requires tractable models for analyzing and predicting the behavior of neurons and networks. The generalized linear model (GLM) is an increasingly popular statistical framework for analyzing neural…

Neural and Evolutionary Computing · Computer Science 2014-04-09 Jonathon Shlens

Perceptions and actions, thoughts and memories result from coordinated activity in hundreds or even thousands of neurons in the brain. It is an old dream of the physics community to provide a statistical mechanics description for these and…

Disordered Systems and Neural Networks · Physics 2024-09-04 Leenoy Meshulam , William Bialek

In the theory of social choice the research is focused around the projection of individual preference orders to the social preference order. Also, the justification of the preference order formalism begins with the concept of utility i.e.…

Computer Science and Game Theory · Computer Science 2010-10-27 Redjan F. Shabani

The definition of preferences assigned to individuals is a concept that concerns many disciplines, from economics, with the search of an acceptable outcome for an ensemble of individuals, to decision making an analysis of vote systems. We…

Physics and Society · Physics 2008-12-02 Elena Ramirez Barrios , Juan G. Diaz Ochoa