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The goal of this thesis is to improve our understanding of the internal mechanisms by which deep artificial neural networks create meaningful representations and are able to generalize. We focus on the challenge of characterizing the…

Machine Learning · Computer Science 2025-10-29 Diego Doimo

Frequentists' inference often delivers point estimators associated with confidence intervals or sets for parameters of interest. Constructing the confidence intervals or sets requires understanding the sampling distributions of the point…

Statistics Theory · Mathematics 2016-10-18 Xinran Li , Peng Ding

This paper introduces a novel concept of interval probability measures that enables the representation of imprecise probabilities, or uncertainty, in a natural and coherent manner. Within an algebra of sets, we introduce a notion of weak…

Statistics Theory · Mathematics 2024-02-06 Marcello Basili , Luca Pratelli

Based on the form invariance of the structures given by Khinchin's axiomatic foundations of information theory and the pseudoadditivity of the Tsallis entropy indexed by q, the concept of conditional entropy is generalized to the case of…

Quantum Physics · Physics 2009-11-06 Sumiyoshi Abe , A. K. Rajagopal

Gibbs' theorem, which is originally intended for canonical ensembles with complete statistics has been generalized to open systems with incomplete statistics. As a result of this generalization, it is shown that the stationary equilibrium…

Statistical Mechanics · Physics 2015-05-13 G. B. Bagci

We define a general notion of entropy in elementary, algebraic terms. Based on that, weak forms of a scalar product and a distance measure are derived. We give basic properties of these quantities, generalize the Cauchy-Schwarz inequality,…

Spectral Theory · Mathematics 2024-04-10 Martin Schlather

Previously referred to as `miraculous' in the scientific literature because of its powerful properties and its wide application as optimal solution to the problem of induction/inference, (approximations to) Algorithmic Probability (AP) and…

Information Theory · Computer Science 2018-04-16 Hector Zenil , Liliana Badillo , Santiago Hernández-Orozco , Francisco Hernández-Quiroz

Brandenburger, Friedenberg, and Keisler provide an epistemic characterization of iterated admissibility (i.e., iterated deletion of weakly dominated strategies) where uncertainty is represented using LPSs (lexicographic probability…

Artificial Intelligence · Computer Science 2009-06-24 Joseph Y. Halpern , Rafael Pass

We study the distributions of the random Dirichlet series with parameters $(s, \beta)$ defined by $$ S=\sum_{n=1}^{\infty}\frac{I_n}{n^s}, $$ where $(I_n)$ is a sequence of independent Bernoulli random variables, $I_n$ taking value $1$ with…

Probability · Mathematics 2016-01-01 Ron Peled , Yuval Peres , Jim Pitman , Ryokichi Tanaka

In "Reliable Communication in the Absence of a Common Clock" (Yeung et al., 2009), the authors introduce general run-length sets, which form a class of constrained systems that permit run-lengths from a countably infinite set. For a…

Information Theory · Computer Science 2010-01-14 Georg Böcherer , Rudolf Mathar , Valdemar Cardoso da Rocha Junior , Cecilio Pimentel

We investigate the overdamped stochastic dynamics of a particle in an asymptotically flat external potential field, in contact with a thermal bath. For an infinite system size, the particles may escape the force field and diffuse freely at…

Statistical Mechanics · Physics 2020-06-24 Erez Aghion , David A. Kessler , Eli Barkai

The concept of distinguishability lies at the heart of quantum information theory. We introduce \textit{left-right relative entropy} as a quantitative measure of distinguishability within the space of boundary states in two-dimensional…

High Energy Physics - Theory · Physics 2026-05-26 Mostafa Ghasemi

We provide a general theorem on the asymptotic behavior of stochastic processes that conform to a relaxed supermartingale condition. The distinguishing feature of our result is that it provides quantitative convergence guarantees at a much…

Optimization and Control · Mathematics 2026-05-11 Morenikeji Neri , Nicholas Pischke , Thomas Powell

Drees and Rootz\'en (2010) have established limit theorems for a general class of empirical processes of statistics that are useful for the extreme value analysis of time series, but do not apply to statistics of sliding blocks, including…

Statistics Theory · Mathematics 2020-09-02 Holger Drees , Sebastian Neblung

In this paper, we evolve from sparsity, a key concept in robust statistics, to concepts and theoretical results of what we call the mathematics of resilience, at the interface between category theory, the theory of dynamical systems,…

Information Theory · Computer Science 2020-12-14 Dominique Pastor , Erwan Beurier , Andrée C. Ehresmann , Roger Waldeck

The notion of density of a finite set is introduced. We prove a general theorem of set theory which refines the Gibbs, Bose--Einstein, and Pareto distributions as well as the Zipf law.

Physics and Society · Physics 2007-05-23 V. P. Maslov

There are several ways to measure the compressibility of a random measure; they include general approaches such as using the rate-distortion curve, as well as more specific notions, such as the Renyi information dimension (RID). The RID…

Information Theory · Computer Science 2022-03-09 Mohammad-Amin Charusaie , Arash Amini , Stefano Rini

For any class of operators which transform unary total functions in the set of natural numbers into functions of the same kind, we define what it means for a real function to be uniformly computable or conditionally computable with respect…

Logic · Mathematics 2013-10-23 Ivan Georgiev , Dimiter Skordev

In this paper, we investigate the asymptotic stability of finite-dimensional stochastic integrable Hamiltonian systems via information entropy. Specifically, we establish the asymptotic vanishing of Shannon entropy difference (with…

Dynamical Systems · Mathematics 2025-10-28 Chen Wang , Yong Li

Copulas are known to satisfy a number of regularity properties, and one might therefore believe that their densities, when they exist, admit a certain degree of regularity themselves. We show that this is not true in general by constructing…

Probability · Mathematics 2022-04-12 Michaël Lalancette , Robert Zimmerman
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