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Related papers: Influences in Mixing Measures

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A critical step for reliable large language models (LLMs) use in healthcare is to attribute predictions to their training data, akin to a medical case study. This requires token-level precision: pinpointing not just which training examples…

Machine Learning · Computer Science 2026-05-14 Shixing Yu , Promit Ghosal , Kyra Gan

This work analyses surprising elections, and attempts to quantify the notion of surprise in elections. A voter is surprised if their estimate of the winner (assumed to be based on a combination of the preferences of their social connections…

Social and Information Networks · Computer Science 2018-11-26 Sagar Massand , Swaprava Nath

This paper deals with a new measure of the influence of each feature on the response variable in classification problems, accounting for potential dependencies among certain feature subsets. Within this framework, we consider a sample of…

Optimization and Control · Mathematics 2024-08-06 Laura Davila-Pena , Alejandro Saavedra-Nieves , Balbina Casas-Méndez

A Boolean function $f:\{0,1\}^n \to \{0,1\}$ is said to be noise sensitive if inserting a small random error in its argument makes the value of the function almost unpredictable. Benjamini, Kalai and Schramm showed that if the sum of…

Combinatorics · Mathematics 2010-03-10 Nathan Keller , Guy Kindler

The integrity of elections is central to democratic systems. However, a myriad of malicious actors aspire to influence election outcomes for financial or political benefit. A common means to such ends is by manipulating perceptions of the…

Computer Science and Game Theory · Computer Science 2022-06-22 Junlin Wu , Andrew Estornell , Lecheng Kong , Yevgeniy Vorobeychik

Machine learning systems increasingly depend on pipelines of multiple algorithms to provide high quality and well structured predictions. This paper argues interaction effects between clustering and prediction (e.g. classification,…

Machine Learning · Statistics 2019-01-01 Matt Barnes , Artur Dubrawski

The seminal result of Kahn, Kalai and Linial shows that a coalition of $O(\frac{n}{\log n})$ players can bias the outcome of any Boolean function $\{0,1\}^n \to \{0,1\}$ with respect to the uniform measure. We extend their result to…

Discrete Mathematics · Computer Science 2019-02-21 Yuval Filmus , Lianna Hambardzumyan , Hamed Hatami , Pooya Hatami , David Zuckerman

We study the problem of reconstructing the probability measure of the Curie-Weiss model from a sample of the voting behaviour of a subset of the population. While originally used to study phase transitions in statistical mechanics, the…

Probability · Mathematics 2025-08-06 Miguel Ballesteros , Ivan Naumkin , Gabor Toth

We study the Shapley value in weighted voting games. The Shapley value has been used as an index for measuring the power of individual agents in decision-making bodies and political organizations, where decisions are made by a majority vote…

Computer Science and Game Theory · Computer Science 2014-08-05 Joel Oren , Yuval Filmus , Yair Zick , Yoram Bachrach

The effect of Richard T. Cox's contribution to probability theory was to generalize Boolean implication among logical statements to degrees of implication, which are manipulated using rules derived from consistency with Boolean algebra.…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Kevin H. Knuth

The network influence model is a model for binary outcome variables that accounts for dependencies between outcomes for units that are relationally tied. The basic influence model was previously extended to afford a suite of new dependence…

Methodology · Statistics 2022-03-09 Johan Koskinen , Galina Daraganova

We investigate the application of matrix product state (MPS) representations of the influence functionals (IF) for the calculation of real-time equilibrium correlation functions in open quantum systems. Focusing specifically on the unbiased…

Modern deep learning models for NLP are notoriously opaque. This has motivated the development of methods for interpreting such models, e.g., via gradient-based saliency maps or the visualization of attention weights. Such approaches aim to…

Computation and Language · Computer Science 2020-05-15 Xiaochuang Han , Byron C. Wallace , Yulia Tsvetkov

Interest is growing in social learning models where users share opinions and adjust their beliefs in response to others. This paper introduces generalized-bias opinion models, an extension of the DeGroot model, that captures a broader range…

Social and Information Networks · Computer Science 2024-09-18 Juan Paz , Camilo Rocha , Luis Tobòn , Frank Valencia

Understanding political phenomena requires measuring the political preferences of society. We introduce a model based on mixtures of spatial voting models that infers the underlying distribution of political preferences of voters with only…

Computers and Society · Computer Science 2016-10-27 Alison Nahm , Alex Pentland , Peter Krafft

Results of measurements give legitimacy to a physical theory. What if acquiring these results in the first place necessitates what the same theory considers to be an interaction? In this note, we assume that theories account for…

Quantum Physics · Physics 2019-05-01 Arne Hansen , Stefan Wolf

Random factor graphs provide a powerful framework for the study of inference problems such as decoding problems or the stochastic block model. Information-theoretically the key quantity of interest is the mutual information between the…

Discrete Mathematics · Computer Science 2021-04-27 Amin Coja-Oghlan , Max Hahn-Klimroth , Philipp Loick , Noela Müller , Konstantinos Panagiotou , Matija Pasch

Coalitional voting games appear in different forms in multi-agent systems, social choice and threshold logic. In this paper, the complexity of comparison of influence between players in coalitional voting games is characterized. The…

Computer Science and Game Theory · Computer Science 2008-09-04 Haris Aziz

We report an inconsistency found in probability theory (also referred to as measure-theoretic probability). For probability measures induced by real-valued random variables, we deduce an "equality" such that one side of the "equality" is a…

General Mathematics · Mathematics 2017-03-01 Guang-Liang Li , Victor O. K. Li

Measurements play a crucial role in doing physics: Their results provide the basis on which we adopt or reject physical theories. In this note, we examine the effect of subjecting measurements themselves to our experience. We require that…

Quantum Physics · Physics 2020-01-28 Arne Hansen , Stefan Wolf