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Active inference has emerged as an alternative approach to control problems given its intuitive (probabilistic) formalism. However, despite its theoretical utility, computational implementations have largely been restricted to…

Machine Learning · Computer Science 2022-03-01 Aswin Paul , Noor Sajid , Manoj Gopalkrishnan , Adeel Razi

How can we explain the predictions of a black-box model? In this paper, we use influence functions -- a classic technique from robust statistics -- to trace a model's prediction through the learning algorithm and back to its training data,…

Machine Learning · Statistics 2021-01-01 Pang Wei Koh , Percy Liang

Our preferences depend on the circumstances in which we reveal them. We will introduce a dependency which allows us to illustrate the relation between the possibility of winning of particular candidates in a quantum election and the type of…

Quantum Physics · Physics 2015-05-27 Marcin Makowski , Edward W. Piotrowski

We study the dynamics of public opinion in a model in which agents change their opinions as a result of random binary encounters if the opinion difference is below their individual thresholds that evolve over time. We ground these…

Physics and Society · Physics 2007-12-10 Gani Aldashev , Timoteo Carletti

Participatory budgeting is a democratic approach to deciding the funding of public projects, which has been adopted in many cities across the world. We present a survey of research on participatory budgeting emerging from the computational…

Computer Science and Game Theory · Computer Science 2020-03-03 Haris Aziz , Nisarg Shah

Visual statistical inference is a way to determine significance of patterns found while exploring data. It is dependent on the evaluation of a lineup, of a data plot among a sample of null plots, by human observers. Each individual is…

Applications · Statistics 2014-08-12 Mahbubul Majumder , Heike Hofmann , Dianne Cook

Off-policy evaluation in reinforcement learning offers the chance of using observational data to improve future outcomes in domains such as healthcare and education, but safe deployment in high stakes settings requires ways of assessing its…

Machine Learning · Computer Science 2020-08-12 Omer Gottesman , Joseph Futoma , Yao Liu , Sonali Parbhoo , Leo Anthony Celi , Emma Brunskill , Finale Doshi-Velez

Evaluation is the central means for assessing, understanding, and communicating about NLP models. In this position paper, we argue evaluation should be more than that: it is a force for driving change, carrying a sociological and political…

Computation and Language · Computer Science 2022-12-23 Rishi Bommasani

In a signed graph, each link is labeled with either a positive or a negative sign. This is particularly appropriate to model polarized systems. Such a graph can be characterized through the notion of structural balance, which relies on the…

Social and Information Networks · Computer Science 2019-05-01 Nejat Arinik , Rosa Figueiredo , Vincent Labatut

Extension problems for polynomial valuations on different cones of convex functions are investigated. It is shown that for the classes of functions under consideration, the extension problem reduces to a simple geometric obstruction on the…

Functional Analysis · Mathematics 2024-08-14 Jonas Knoerr , Jacopo Ulivelli

This paper offers a synthesis of the empirical literature on the effects of monetary policy. Using the findings from an extensive collection of meta-analyses, it evaluates the effectiveness of conventional and unconventional monetary policy…

Theoretical Economics · Economics 2025-09-25 Ricardo Alonzo Fernandez Salguero

The related concepts of partisan belief systems, issue alignment, and partisan sorting are central to our understanding of politics. These phenomena have been studied using measures of alignment between pairs of topics, or how much…

Social and Information Networks · Computer Science 2025-01-14 Letizia Iannucci , Ali Faqeeh , Ali Salloum , Ted Hsuan Yun Chen , Mikko Kivelä

In democracies, major policy decisions typically require some form of majority or consensus, so elites must secure mass support to govern. Historically, elites could shape support only through limited instruments like schooling and mass…

General Economics · Economics 2025-12-04 Nadav Kunievsky

We investigate a dynamical model of opinion formation in which an individual's opinion is influenced by interactions with a group of other agents. We introduce a bias towards one of the opinions in a manner not considered earlier to the…

Physics and Society · Physics 2024-09-17 Pratik Mullick , Parongama Sen

Selection as Power argued that upstream selection authority, rather than internal objective misalignment, constitutes a primary source of risk in high-stakes agentic systems. However, the original framework was static: governance…

Multiagent Systems · Computer Science 2026-03-03 Jose Manuel de la Chica Rodriguez , Juan Manuel Vera Díaz

In recent years, enlargement of the European Union has led to increased interest in the allocation of voting weights to member states with hugely differing population numbers. While the eventually agreed voting scheme lacks any strict…

General Mathematics · Mathematics 2008-09-11 Martin Kurth

Two of the main factors shaping an individual's opinion are social coordination and personal preferences, or personal biases. To understand the role of those and that of the topology of the network of interactions, we study an extension of…

Physics and Society · Physics 2023-06-07 Filippo Zimmaro , Pierluigi Contucci , János Kertész

I devise a novel approach to evaluate the effectiveness of fiscal policy in the short run with multi-category treatment effects and inverse probability weighting based on the potential outcome framework. This study's main contribution to…

Econometrics · Economics 2020-08-11 Koiti Yano

When language models answer open-ended problems, they implicitly make hidden decisions that shape their outputs, leaving users with uncontextualized answers rather than a working map of the problem; drawing on multiverse analysis from…

Human-Computer Interaction · Computer Science 2026-05-05 Andre Ye , Jenny Y. Huang , Alicia Guo , Rose Novick , Tamara Broderick , Mitchell L. Gordon

We revisit and generalize the concept of composite likelihood as a method to make a probabilistic inference by aggregation of multiple Bayesian agents, thereby defining a class of predictive models which we call composite Bayesian. This…

Computation · Statistics 2019-04-18 Alexis Roche