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Early theories of perception as probabilistic inference propose that uncertainty about the interpretation of sensory input is represented as a probability distribution over many interpretations -- a relatively complex representation.…

Neurons and Cognition · Quantitative Biology 2025-10-01 Andrew Jun Lee , Daniel Turek , Omer Daglar Tanrikulu

In this paper, it is shown that a simple formulation of Economic Model Predictive Control can be used which possesses two features that are generally viewed as mutually exclusive, namely, a rather short prediction horizon…

Systems and Control · Electrical Eng. & Systems 2020-11-23 Mazen Alamir , Gabriele Pannochia

All scientific interpretations of statistical outputs depend on background (auxiliary) assumptions that are rarely delineated or explicitly interrogated. These include not only the usual modeling assumptions, but also deeper assumptions…

Methodology · Statistics 2022-08-01 Sander Greenland , Zad Rafi , Robert Matthews , Megan Higgs

This paper analyzes a society composed of individuals who have diverse sets of beliefs (or models) and diverse tastes (or utility functions). It characterizes the model selection process of a social planner who wishes to aggregate…

Theoretical Economics · Economics 2026-02-10 Florian Mudekereza

Given only aggregate choice data and limited information about how menus are distributed across the population, we describe what can be inferred robustly about the distribution of preferences (or more general decision rules). We strengthen…

Theoretical Economics · Economics 2024-05-16 Larry G Epstein , Kaushil Patel

Different types of reasoning impose different structural demands on representational systems, yet no systematic account of these demands exists across psychology, AI, and philosophy of mind. I propose a framework identifying four structural…

Artificial Intelligence · Computer Science 2026-04-03 Yiling Wu

Abstract argumentation has emerged as a method for non-monotonic reasoning that has gained popularity in the symbolic artificial intelligence community. In the literature, the different approaches to abstract argumentation that were refined…

Artificial Intelligence · Computer Science 2021-01-11 Timotheus Kampik , Juan Carlos Nieves

We propose a simple and general framework for nonparametric estimation of heterogeneous treatment effects under fairness constraints. Under standard regularity conditions, we show that the resulting estimators possess the double robustness…

Methodology · Statistics 2023-12-21 Kwangho Kim , José R. Zubizarreta

The unit selection problem aims to identify a set of individuals who are most likely to exhibit a desired mode of behavior, for example, selecting individuals who would respond one way if encouraged and a different way if not encouraged.…

Artificial Intelligence · Computer Science 2022-08-23 Ang Li , Judea Pearl

Understanding the mechanisms underlying the formation of cultural traits, such as preferences, opinions and beliefs is an open challenge. Trait formation is intimately connected to cultural dynamics, which has been the focus of a variety of…

Physics and Society · Physics 2018-12-27 Alexandru-Ionuţ Băbeanu , Diego Garlaschelli

We show that many bounded rationality patterns of choice can be alternatively represented as testable models of limited consideration, and we elicit the features of the associated unobserved consideration sets from the observed choice.…

Theoretical Economics · Economics 2024-03-08 Davide Carpentiere , Angelo Petralia

Local variable selection aims to test for the effect of covariates on an outcome within specific regions. We outline a challenge that arises in the presence of non-linear effects and model misspecification. Specifically, for common…

Methodology · Statistics 2024-08-02 David Rossell , Arnold Kisuk Kseung , Ignacio Saez , Michele Guindani

Multicriteria decision analysis aims at supporting a person facing a decision problem involving conflicting criteria. We consider an additive utility model which provides robust conclusions based on preferences elicited from the decision…

Artificial Intelligence · Computer Science 2015-02-17 K. Belahcene , C. Labreuche , N. Maudet , V. Mousseau , W. Ouerdane

We consider functional linear regression models where functional outcomes are associated with scalar predictors by coefficient functions with shape constraints, such as monotonicity and convexity, that apply to sub-domains of interest. To…

Methodology · Statistics 2025-05-09 Kyunghee Han , Yeonjoo Park , Soo-Young Kim

Selective rationalization aims to produce decisions along with rationales (e.g., text highlights or word alignments between two sentences). Commonly, rationales are modeled as stochastic binary masks, requiring sampling-based gradient…

Computation and Language · Computer Science 2021-09-13 Nuno Miguel Guerreiro , André F. T. Martins

Economic choices are often stochastic: the same person may make a different choice when facing the same alternatives repeatedly. Standard models assume that the degree of randomness reflects the size of utility differences, but choice…

Theoretical Economics · Economics 2026-05-05 Shuhua Si

We investigate activities that have different periods of duration. We define the profit intensity as a measure of this economic category. The profit intensity in a repeated trading has a unique property of attaining its maximum at a fixed…

Trading and Market Microstructure · Quantitative Finance 2009-11-13 Edward W. Piotrowski , Jan Sladkowski

We study welfare analysis for policy changes when supply and demand behavior are only partially known. We augment the robust approach pioneered by Kang and Vasserman (2025) by incorporating the supply side. We posit intervals of feasible…

Theoretical Economics · Economics 2026-04-29 Konstantin von Beringe , Mark Whitmeyer

This paper investigates the use of synthetic control methods for causal inference in macroeconomic settings when dealing with possibly nonstationary data. While the synthetic control approach has gained popularity for estimating…

Econometrics · Economics 2025-05-29 Zhentao Shi , Jin Xi , Haitian Xie

Prediction+optimization is a common real-world paradigm where we have to predict problem parameters before solving the optimization problem. However, the criteria by which the prediction model is trained are often inconsistent with the goal…

Machine Learning · Computer Science 2021-11-23 Kai Yan , Jie Yan , Chuan Luo , Liting Chen , Qingwei Lin , Dongmei Zhang
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