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The binary Euclidean algorithm is a variant of the classical Euclidean algorithm. It avoids multiplications and divisions, except by powers of two, so is potentially faster than the classical algorithm on a binary machine. We describe the…

Data Structures and Algorithms · Computer Science 2013-03-13 Richard P. Brent

D. Hensley showed in 1994 that the number of steps taken by the Euclidean algorithm to find the greatest common divisor of two natural numbers less than or equal to n follows a normal distribution in the limit as n tends to infinity. V.…

Dynamical Systems · Mathematics 2015-02-27 Ian D. Morris

The problem is considered of arranging symbols around a cycle, in such a way that distances between different instances of a same symbol be as uniformly distributed as possible. A sequence of moments is defined for cycles, similarly to the…

Data Structures and Algorithms · Computer Science 2018-04-05 Luca Ghezzi , Roberto Baldacci

The distributional analysis of Euclidean algorithms was carried out by Baladi and Vall\'{e}e. They showed the asymptotic normality of the number of division steps and associated costs in the Euclidean algorithm as a random variable on the…

Dynamical Systems · Mathematics 2025-10-27 Dohyeong Kim , Jungwon Lee , Seonhee Lim

This study provides new results about the probabilistic behaviour of a class of Euclidean algorithms: the asymptotic distribution of a whole class of cost-parameters associated to these algorithms is normal. For the cost corresponding to…

Data Structures and Algorithms · Computer Science 2007-05-23 Viviane Baladi , Brigitte Vallee

We propose a fast, distance-preserving, binary embedding algorithm to transform a high-dimensional dataset $\mathcal{T}\subseteq\mathbb{R}^n$ into binary sequences in the cube $\{\pm 1\}^m$. When $\mathcal{T}$ consists of well-spread (i.e.,…

Information Theory · Computer Science 2021-03-11 Jinjie Zhang , Rayan Saab

We consider the problem of encoding a set of vectors into a minimal number of bits while preserving information on their Euclidean geometry. We show that this task can be accomplished by applying a Johnson-Lindenstrauss embedding and…

Information Theory · Computer Science 2022-04-12 Sjoerd Dirksen , Alexander Stollenwerk

In this article, we prove the existence and uniqueness of a certain distribution function on the unit interval. This distribution appears in Brent's model of the analysis of the binary gcd algorithm. The existence and uniqueness of such a…

General Mathematics · Mathematics 2010-06-11 Gerard Maze

The Brent-McMillan algorithm B3 (1980), when implemented with binary splitting, is the fastest known algorithm for high-precision computation of Euler's constant. However, no rigorous error bound for the algorithm has ever been published.…

Numerical Analysis · Mathematics 2015-08-18 Richard P. Brent , Fredrik Johansson

A new methodology is proposed for generating realizations of a random vector with values in a finite-dimensional Euclidean space that are statistically consistent with a data set of observations of this vector. The probability distribution…

Probability · Mathematics 2016-08-24 Christian Soize , Roger Ghanem

Although recovering an Euclidean distance matrix from noisy observations is a common problem in practice, how well this could be done remains largely unknown. To fill in this void, we study a simple distance matrix estimate based upon the…

Machine Learning · Statistics 2014-09-18 Luwan Zhang , Grace Wahba , Ming Yuan

An iterative randomness extraction algorithm which generalized the Von Neumann's extraction algorithm is detailed, analyzed and implemented in standard C++. Given a sequence of independently and identically distributed biased Bernoulli…

Information Theory · Computer Science 2021-01-08 Claude Gravel

A computational theory for clustering and a semi-supervised clustering algorithm is presented. Clustering is defined to be the obtainment of groupings of data such that each group contains no anomalies with respect to a chosen grouping…

Machine Learning · Computer Science 2025-07-17 Nassir Mohammad

2-Opt is probably the most basic local search heuristic for the TSP. This heuristic achieves amazingly good results on real world Euclidean instances both with respect to running time and approximation ratio. There are numerous experimental…

Data Structures and Algorithms · Computer Science 2023-02-15 Matthias Englert , Heiko Röglin , Berthold Vöcking

We observe structure in the sequences of quotients and remainders of the Euclidean algorithm with two families of inputs. Analyzing the remainders, we obtain new algorithms for computing modular inverses and representating prime numbers by…

Number Theory · Mathematics 2017-04-05 Christina Doran , Shen Lu , Barry R. Smith

In this thesis I discuss combinatorial optimization problems, from the statistical physics perspective. The starting point are the motivations which brought physicists together with computer scientists and mathematicians to work on this…

Disordered Systems and Neural Networks · Physics 2020-01-13 Andrea Di Gioacchino

The Euclidean algorithm is one of the oldest algorithms known to mankind. Given two integral numbers $a_1$ and $a_2$, it computes the greatest common divisor (gcd) of $a_1$ and $a_2$ in a very elegant way. From a lattice perspective, it…

Data Structures and Algorithms · Computer Science 2023-11-28 Kim-Manuel Klein , Janina Reuter

A modified form of Euclid's algorithm has gained popularity among musical composers following Toussaint's 2005 survey of so-called Euclidean rhythms in world music. We offer a method to easily calculate Euclid's algorithm by hand as a…

History and Overview · Mathematics 2022-06-28 Thomas Morrill

We describe an exact algorithm for finding the best 2-OPT move which, experimentally, was observed to be much faster than the standard quadratic approach. To analyze its average-case complexity, we introduce a family of heuristic procedures…

Data Structures and Algorithms · Computer Science 2024-04-01 Giuseppe Lancia , Paolo Vidoni

The objective of ordinal embedding is to find a Euclidean representation of a set of abstract items, using only answers to triplet comparisons of the form "Is item $i$ closer to the item $j$ or item $k$?". In recent years, numerous…

Machine Learning · Computer Science 2021-10-22 Leena Chennuru Vankadara , Siavash Haghiri , Michael Lohaus , Faiz Ul Wahab , Ulrike von Luxburg
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