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Related papers: "How many $1$'s are needed?" revisited

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In this work we study the space complexity of computable real numbers represented by fast convergent Cauchy sequences. We show the existence of families of trascendental numbers which are logspace computable, as opposed to algebraic…

Computational Complexity · Computer Science 2018-05-08 Masaki Nakanishi , Marcos Villagra

This paper studies the minimal length representation of the natural numbers. Let O be a fixed set of integer-valued functions (primarily hyperoperations). For each n, what is the shortest way of expressing n as a combinations of functions…

History and Overview · Mathematics 2018-01-08 Akshunna Shaurya Dogra

A decomposition of a natural number n is a sequence of consecutive natural numbers that sums to n. We construct a one-to-one correspondence between the odd factors of a natural number and its decompositions. We study the decompositions by…

History and Overview · Mathematics 2007-05-23 Wai Yan Pong

We present a general method for computing the abelian complexity $\rho^{\rm ab}_{\bf s} (n)$ of an automatic sequence $\bf s$ in the case where (a) $\rho^{\rm ab}_{\bf s} (n)$ is bounded by a constant and (b) the Parikh vectors of the…

Formal Languages and Automata Theory · Computer Science 2020-11-17 Jeffrey Shallit

We study formal languages which are capable of fully expressing quantitative probabilistic reasoning and do-calculus reasoning for causal effects, from a computational complexity perspective. We focus on satisfiability problems whose…

Artificial Intelligence · Computer Science 2023-05-17 Benito van der Zander , Markus Bläser , Maciej Liśkiewicz

We comment on a recent paper by D'Abramo [Chaos, Solitons & Fractals, 25 (2005) 29], focusing on the author's statement that an algorithm can produce a list of strings containing at least one string whose algorithmic complexity is greater…

Computational Complexity · Computer Science 2011-11-09 David Poulin , Hugo Touchette

In this article some difficulties are deduced from the set of natural numbers. By using the method of transfinite recursion we define an iterative process which is designed to deduct all the non-greatest elements of the set of natural…

General Mathematics · Mathematics 2013-12-18 Qiu Kui Zhang

This paper concerns the question to what extent it can be efficiently determined whether an arbitrary program correctly solves a given problem. This question is investigated with programs of a very simple form, namely instruction sequences,…

Logic in Computer Science · Computer Science 2019-11-22 J. A. Bergstra , C. A. Middelburg

We consider representing of natural numbers by expressions using 1's, addition, multiplication and parentheses. $\left\| n \right\|$ denotes the minimum number of 1's in the expressions representing $n$. The logarithmic complexity $\left\|…

Number Theory · Mathematics 2014-09-02 Juris Čerņenoks , Jānis Iraids , Mārtiņš Opmanis , Rihards Opmanis , Kārlis Podnieks

In the first part of this paper, we present a unified framework for analyzing the algorithmic complexity of any optimization problem, whether it be continuous or discrete in nature. This helps to formalize notions like "input", "size" and…

Optimization and Control · Mathematics 2022-07-06 Amitabh Basu

Depth is a complexity measure for natural systems of the kind studied in statistical physics and is defined in terms of computational complexity. Depth quantifies the length of the shortest parallel computation required to construct a…

Popular Physics · Physics 2011-11-14 Jon Machta

This paper investigates a variant of the famous "happy numbers" sequence, given by A351327 on the oeis. First of all we'll define this integer sequence, and then we'll show some important results about it; in particular we conjectured that…

General Mathematics · Mathematics 2022-03-08 Luca Onnis

Classically, the time complexity of a first-order method is estimated by its number of gradient computations. In this paper, we study a more refined complexity by taking into account the `lingering' of gradients: once a gradient is computed…

Optimization and Control · Mathematics 2019-05-29 Zeyuan Allen-Zhu , David Simchi-Levi , Xinshang Wang

The intuition that a long history is required for the emergence of complexity in natural systems is formalized using the notion of depth. The depth of a system is defined in terms of the number of parallel computational steps needed to…

Statistical Mechanics · Physics 2011-11-09 J. Machta

While concepts and tools from Theoretical Computer Science are regularly applied to, and significantly support, software development for discrete problems, Numerical Engineering largely employs recipes and methods whose correctness and…

Computational Complexity · Computer Science 2018-01-23 Akitoshi Kawamura , Martin Ziegler

We offer multiplication method for factoring big natural numbers which extends the group of the Fermat's and Lehman's factorization algorithms and has run-time complexity $O(n^{1/3})$. This paper is argued the finiteness of proposed…

Data Structures and Algorithms · Computer Science 2019-04-01 Igor Nesiolovskiy , Artem Nesiolovskiy

G. Edelman, O. Sporns, and G. Tononi have introduced the neural complexity of a family of random variables, defining it as a specific average of mutual information over subfamilies. We show that their choice of weights satisfies two natural…

Probability · Mathematics 2009-12-21 Jerome Buzzi , Lorenzo Zambotti

We study multivariate problems like function approximation, numerical integration, global optimization and dispersion. We obtain new results on the information complexity $n(\varepsilon,d)$ of these problems. The information complexity is…

Numerical Analysis · Mathematics 2019-05-06 David Krieg

We present a uniform description of sets of $m$ linear forms in $n$ variables over the field of rational numbers whose computation requires $m(n - 1)$ additions.

Computational Complexity · Computer Science 2022-12-13 Michael Kaminski , Igor E. Shparlinski , Michel Waldschmidt

Bayesian Networks (BNs) are useful tools giving a natural and compact representation of joint probability distributions. In many applications one needs to learn a Bayesian Network (BN) from data. In this context, it is important to…

Machine Learning · Computer Science 2012-07-02 Or Zuk , Shiri Margel , Eytan Domany