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In the literature, we have various ways of proving irrationality of a real number. In this survey article, we shall emphasize on a particular criterion to prove irrationality. This is called nice approximation of a number by a sequence of…

Number Theory · Mathematics 2022-06-28 Tirthankar Bhattacharyya , Soham Bakshi , Arka Das

The quantization scheme in probability theory deals with finding a best approximation of a given probability distribution by a probability distribution that is supported on finitely many points. In this paper, first we state and prove a…

Probability · Mathematics 2023-05-05 Juan Gomez , Haily Martinez , Mrinal K. Roychowdhury , Alexis Salazar , Daniel J. Vallez

A finite form of de Finetti's representation theorem is established using elementary information-theoretic tools: The distribution of the first $k$ random variables in an exchangeable binary vector of length $n\geq k$ is close to a mixture…

Information Theory · Computer Science 2021-06-28 Lampros Gavalakis , Ioannis Kontoyiannis

This paper provides a quantitative version of de Finetti law of large numbers. Given an infinite sequence $\{X_n\}_{n \geq 1}$ of exchangeable Bernoulli variables, it is well-known that $\frac{1}{n} \sum_{i = 1}^n X_i…

Probability · Mathematics 2020-09-22 Emanuele Dolera , Stefano Favaro

The problem addressed concerns the determination of the average number of successive attempts of guessing a word of a certain length consisting of letters with given probabilities of occurrence. Both first- and second-order approximations…

Information Theory · Computer Science 2015-06-19 Kerstin Andersson

How to generate provably true randomness with minimal assumptions? This question is important not only for the efficiency and the security of information processing, but also for understanding how extremely unpredictable events are possible…

Quantum Physics · Physics 2015-05-18 Kai-Min Chung , Yaoyun Shi , Xiaodi Wu

We consider the problem of rationalizing choice data by a preference satisfying an arbitrary collection of invariance axioms. Examples of such axioms include quasilinearity, homotheticity, independence-type axioms for mixture spaces,…

Theoretical Economics · Economics 2024-08-09 Peter Caradonna , Christopher P. Chambers

We study a class of nonlinear nonparametric inverse problems. Specifically, we propose a nonparametric estimator of the dynamics of a monotonically increasing trajectory defined on a finite time interval. Under suitable regularity…

Statistics Theory · Mathematics 2014-08-25 Debashis Paul , Jie Peng , Prabir Burman

The widely claimed replicability crisis in science may lead to revised standards of significance. The customary frequentist confidence intervals, calibrated through hypothetical repetitions of the experiment that is supposed to have…

Statistics Theory · Mathematics 2020-02-11 Luigi Pace , Alessandra Salvan

Using techniques from Poisson approximation, we prove explicit error bounds on the number of permutations that avoid any pattern. Most generally, we bound the total variation distance between the joint distribution of pattern occurrences…

Combinatorics · Mathematics 2023-06-22 Harry Crane , Stephen DeSalvo

We consider the problem of approaching real numbers with rational numbers with prime denominator and with a single numerator allowed for each denominator. We then present a simple application, related to possible correlations between trace…

Number Theory · Mathematics 2023-09-26 Emmanuel Kowalski

Rejection sampling is a popular method used to generate numbers that follow some given distribution. We study the use of this method to generate random numbers in the unit interval from increasing probability density functions. We focus on…

Data Structures and Algorithms · Computer Science 2025-09-30 Louis-Roy Langevin , Alex Waese-Perlman

We study sums of a random multiplicative function; this is an example, of number-theoretic interest, of sums of products of independent random variables (chaoses). Using martingale methods, we establish a normal approximation for the sum…

Number Theory · Mathematics 2010-12-02 Adam J. Harper

We study the use of Temporal-Difference learning for estimating the structural parameters in dynamic discrete choice models. Our algorithms are based on the conditional choice probability approach but use functional approximations to…

Econometrics · Economics 2022-12-23 Karun Adusumilli , Dita Eckardt

The purpose of this article is to formulate a number of probabilistic hidden-variable theorems, to provide proofs in some cases, and counterexamples to some conjectured relationships. The first theorem is the fundamental one. It asserts the…

Quantum Physics · Physics 2008-02-03 Patrick Suppes , J. Acacio de Barros , Gary Oas

Consider a density $f$ on $[0,1]$ that must be estimated from an i.i.d. sample $X_1,...,X_n$ drawn from $f$. In this note, we study binary-tree-based histogram estimates that use recursive splitting of intervals. If the decision to split an…

Statistics Theory · Mathematics 2025-04-24 Luc Devroye , Jad Hamdan

In the setting where we have $n$ independent observations of a random variable $X$, we derive explicit error bounds in total variation distance when approximating the number of observations equal to the maximum of the sample (in the case…

Probability · Mathematics 2026-04-10 Fraser Daly

A key issue in the handling of temporal data is the treatment of persistence; in most approaches it consists in inferring defeasible confusions by extrapolating from the actual knowledge of the history of the world; we propose here a…

Artificial Intelligence · Computer Science 2013-03-08 Dimiter Driankov , Jerome Lang

For the principal eigenvalue of discrete weighted $p$-Laplacian on the set of nonnegative integers, the convergence of an approximation procedure and the inverse iteration is proved. Meanwhile, in the proof of the convergence, the…

Probability · Mathematics 2019-03-11 Yue-Shuang Li

We provide a formal, simple and intuitive theory of rational decision making including sequential decisions that affect the environment. The theory has a geometric flavor, which makes the arguments easy to visualize and understand. Our…

Machine Learning · Computer Science 2012-02-10 Peter Sunehag , Marcus Hutter
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