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Related papers: Algorithm, probability, and prime numbers

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While the prime numbers have been subject to mathematical inquiry since the ancient Greeks, the accumulated effort of understanding these numbers has - as Marcus du Sautoy recently phrased it - 'not revealed the origins of what makes the…

General Mathematics · Mathematics 2018-08-30 Kolbjørn Tunstrøm

The problem of assigning probabilities when little is known is analized in the case where the quanities of interest are physical observables, i.e. can be measured and their values expressed by numbers. It is pointed out that the assignment…

Data Analysis, Statistics and Probability · Physics 2012-08-29 Vesselin I. Dimitrov

Methods of pattern recognition and machine learning are applied extensively in science, technology, and society. Hence, any advances in related theory may translate into large-scale impact. Here we explore how algorithmic information…

Machine Learning · Computer Science 2023-04-05 Kamaludin Dingle , Pau Batlle , Houman Owhadi

Although the likelihood function is normalizeable with respect to the data there is no guarantee that the same holds with respect to the model parameters. This may lead to singularities in the expectation value integral of these parameters,…

Data Analysis, Statistics and Probability · Physics 2007-05-23 R. Preuss , V. Dose

Consider the operation of adding the same number of identical digits to the left and to the right of a number n. In OEIS sequence A090287, it was conjectured that this operation will not produce a prime if and only if n is a palindrome with…

Number Theory · Mathematics 2015-10-22 Chai Wah Wu

We show that there exists a bounded pattern of m consecutive primes for any m>0, that means a tuple H_m of m distinct non-negative integers h_i (i=1,2,...m) such that its translations contain arbitrarily long (finite) arithmetic…

Number Theory · Mathematics 2015-09-08 Janos Pintz

The ``impossibility theorem'' -- which is considered foundational in algorithmic fairness literature -- asserts that there must be trade-offs between common notions of fairness and performance when fitting statistical models, except in two…

Machine Learning · Computer Science 2023-02-14 Andrew Bell , Lucius Bynum , Nazarii Drushchak , Tetiana Herasymova , Lucas Rosenblatt , Julia Stoyanovich

One of the questions of distribution of prime numbers is considered in the article. It is shown what error is obtained from the assumption that the asymptotic density of a sequence of primes is a probability. Various forms of an analogue of…

General Mathematics · Mathematics 2020-12-17 Victor Volfson

We prove the analog of Cram\'er's short intervals theorem for primes in arithmetic progressions and prime ideals, under the relevant Riemann Hypothesis. Both results are uniform in the data of the underlying structure. Our approach is based…

Number Theory · Mathematics 2017-02-15 L. Grenié , G. Molteni , A. Perelli

We have rediscovered a simple algorithm to compute the mathematical constant \[ \pi=3.14159265\cdots. \] The algorithm had been known for a long time but it might not be recognized as a fast, practical algorithm. The time complexity of it…

Number Theory · Mathematics 2019-12-24 Tsz-Wo Sze

We use sets of assignments, a.k.a. teams, and measures on them to define probabilities of first-order formulas in given data. We then axiomatise first-order properties of such probabilities and prove a completeness theorem for our…

Logic · Mathematics 2016-09-09 Tapani Hyttinen , Gianluca Paolini , Jouko Väänänen

Proving programs terminating is a fundamental computer science challenge. Recent research has produced powerful tools that can check a wide range of programs for termination. The analog for probabilistic programs, namely termination with…

Logic in Computer Science · Computer Science 2012-04-16 Javier Esparza , Andreas Gaiser , Stefan Kiefer

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

An open conjecture of Z.-W. Sun states that for any integer $n>1$ there is a positive integer $k\le n$ such that $\pi(kn)$ is prime, where $\pi(x)$ denotes the number of primes not exceeding $x$. In this paper, we show that for any positive…

Number Theory · Mathematics 2020-04-03 Zhi-Wei Sun , Lilu Zhao

In many high-impact applications, it is important to ensure the quality of output of a machine learning algorithm as well as its reliability in comparison with the complexity of the algorithm used. In this paper, we have initiated a…

Machine Learning · Computer Science 2023-03-03 Katarina Doctor , Tong Mao , Hrushikesh Mhaskar

The Lottery Ticket Hypothesis is a conjecture that every large neural network contains a subnetwork that, when trained in isolation, achieves comparable performance to the large network. An even stronger conjecture has been proven recently:…

Machine Learning · Computer Science 2020-10-27 Laurent Orseau , Marcus Hutter , Omar Rivasplata

Two topics of the number theory are discussed in this paper. First, we prove that given each natural number $x\geq10^{3}$, we have \[ |{\rm Li}(x)-\pi(x)|\leq c\sqrt{x}\log x\texttt{ and } \pi(x)={\rm Li}(x)+O(\sqrt{x}\log x) \] where $c$…

General Mathematics · Mathematics 2025-04-02 Shan-Guang Tan

The problem of finding a nontrivial factor of a polynomial f(x) over a finite field F_q has many known efficient, but randomized, algorithms. The deterministic complexity of this problem is a famous open question even assuming the…

Computational Complexity · Computer Science 2019-02-20 Manuel Arora , Gábor Ivanyos , Marek Karpinski , Nitin Saxena

Continuous first-order logic is used to apply model-theoretic analysis to analytic structures (e.g. Hilbert spaces, Banach spaces, probability spaces, etc.). Classical computable model theory is used to examine the algorithmic structure of…

Logic · Mathematics 2008-06-04 Wesley Calvert

One of the core applications of machine learning to knowledge discovery consists on building a function (a hypothesis) from a given amount of data (for instance a decision tree or a neural network) such that we can use it afterwards to…

Machine Learning · Computer Science 2007-05-23 Carlos Domingo , Ricard Gavalda , Osamu Watanabe