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The article explores function terms within uniform theories. It examines the uniformity of these theories through an algebraic lens. The paper compares the uniformity of terms and predicates within axiom schemas. It demonstrates the…

Logic · Mathematics 2024-07-12 Volodymyr Zhuravlov

Quantum coherence characterizes the non-classical feature of a single party system with respect to a local basis. Based on a recently introduced resource framework, coherence can be regarded as a resource and be systematically manipulated…

Quantum Physics · Physics 2018-09-26 Yunchao Liu , Qi Zhao , Xiao Yuan

Partial Information Decomposition (PID) has become one of the most prominent information-theoretic frameworks for describing the structure and quality of information in complex systems. Despite its widespread utility, there exists no unique…

Information Theory · Computer Science 2026-03-10 Alberto Liardi , Keenan J. A. Down , George Blackburne , Matteo Neri , Pedro A. M. Mediano

Approximate co-sufficient sampling (aCSS) offers a principled route to hypothesis testing when null distributions are unknown, yet current implementations are confined to maximum likelihood estimators with smooth or linear regularization…

Methodology · Statistics 2025-06-17 Jie Xie , Dongming Huang

We introduce and study the cumulative information generating function, which provides a unifying mathematical tool suitable to deal with classical and fractional entropies based on the cumulative distribution function and on the survival…

Information Theory · Computer Science 2023-10-12 Marco Capaldo , Antonio Di Crescenzo , Alessandra Meoli

Reliability is an essential measure of how closely observed scores represent latent scores (reflecting constructs), assuming some latent variable measurement model. We present a general theoretical framework of reliability, placing emphasis…

Methodology · Statistics 2024-10-29 Yang Liu , Jolynn Pek , Alberto Maydeu-Olivares

We define a generalized likelihood function based on uncertainty measures and show that maximizing such a likelihood function for different measures induces different types of classifiers. In the probabilistic framework, we obtain…

Machine Learning · Computer Science 2013-01-18 Loo-Nin Teow , Kia-Fock Loe

Probability measures by themselves, are known to be inappropriate for modeling the dynamics of plain belief and their excessively strong measurability constraints make them unsuitable for some representational tasks, e.g. in the context of…

Artificial Intelligence · Computer Science 2013-02-28 Emil Weydert

In this paper we consider an information theoretic approach for the accounting classification process. We propose a matrix formalism and an algorithm for calculations of information theoretic measures associated to accounting…

General Finance · Quantitative Finance 2014-09-30 E. M. S. Ribeiro , G. A. Prataviera

We consider several notions of genericity appearing in algebraic geometry and commutative algebra. Special emphasis is put on various stability notions which are defined in a combinatorial manner and for which a number of equivalent…

Symbolic Computation · Computer Science 2017-05-09 Amir Hashemi , Michael Schweinfurter , Werner M. Seiler

Plausibility measures are structures for reasoning in the face of uncertainty that generalize probabilities, unifying them with weaker structures like possibility measures and comparative probability relations. So far, the theory of…

Quantum Physics · Physics 2015-05-07 Tobias Fritz , Matthew Leifer

Estimation of density functions supported on general domains arises when the data is naturally restricted to a proper subset of the real space. This problem is complicated by typically intractable normalizing constants. Score matching…

Methodology · Statistics 2020-09-25 Shiqing Yu , Mathias Drton , Ali Shojaie

Causality is a central concept in a wide range of research areas, yet there is still no universally agreed axiomatisation of causality. We view causality both as an extension of probability theory and as a study of \textit{what happens when…

Artificial Intelligence · Computer Science 2024-06-07 Junhyung Park , Simon Buchholz , Bernhard Schölkopf , Krikamol Muandet

We take a closer look at the structure of bivariate dependency induced by a pair of predictor random variables $(X_1, X_2)$ trying to synergistically, redundantly or uniquely encode a target random variable $Y$. We evaluate a recently…

Information Theory · Computer Science 2015-03-03 Pradeep Kr. Banerjee

Comparing the top $k$ elements between two or more ranked results is a common task in many contexts and settings. A few measures have been proposed to compare top $k$ lists with attractive mathematical properties, but they face a number of…

Information Theory · Computer Science 2013-10-02 Arun Konagurthu , James Collier

This is a working paper summarizing results of an ongoing research project whose aim is to uniquely characterize the uncertainty measure for the Dempster-Shafer Theory. A set of intuitive axiomatic requirements is presented, some of their…

Artificial Intelligence · Computer Science 2013-02-21 David Harmanec

Information plays an important role in our understanding of the physical world. We hence propose an entropic measure of information for any physical theory that admits systems, states and measurements. In the quantum and classical world,…

Quantum Physics · Physics 2010-05-04 Anthony J. Short , Stephanie Wehner

A concept of the generalized quantum measurement is introduced as the transformation, which establishes a correspondence between the initial states of the object system and final states of the object--measuring device (meter) system with…

Quantum Physics · Physics 2007-05-23 Boris A. Grishanin , Victor N. Zadkov

The representation of a given quantity with less information is often referred to as `quantization' and it is an important subject in information theory. In this paper, we have considered absolutely continuous probability measures on unit…

Probability · Mathematics 2017-07-10 Mrinal Kanti Roychowdhury

The information theoretic quantity known as mutual information finds wide use in classification and community detection analyses to compare two classifications of the same set of objects into groups. In the context of classification…

Social and Information Networks · Computer Science 2020-04-29 M. E. J. Newman , George T. Cantwell , Jean-Gabriel Young
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