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We provide a simple proof that in any homogeneous, compact metric space of diameter $D$, if one finds the average distance $A$ achieved in $X$ with respect to some isometry invariant Borel probability measure, then $$\frac{D}{2} \leq A \leq…

Metric Geometry · Mathematics 2014-07-22 Mark Herman , Jonathan Pakianathan

We introduce a concept of asymptotic mean of digits (symbols) in the $Q_s$-representation of a real number, that is a generalization of the $s$-adic representation and have a self-similar geometry. We discuss its relationship with the…

Number Theory · Mathematics 2026-03-06 M. V. Pratsiovytyi , S. O. Klymchuk

In the preceding decade, Andrews and Newman resurrected the concept of a `minimal excludant' of a partition ($mex$, for short), namely, the least positive missing integer in a partition. Subsequently, several authors have not only studied…

Combinatorics · Mathematics 2026-04-15 Subhash Chand Bhoria , Pramod Eyyunni , Subhrangsu Santra

In the {claw, diamond}-free edge deletion problem, we are given a graph $G$ and an integer $k>0$, the question is whether there are at most $k$ edges whose deletion results in a graph without claws and diamonds as induced graphs. Based on…

Data Structures and Algorithms · Computer Science 2022-01-05 Wenjun Li , Huan Peng , Yongjie Yang

We present a new way to merge any two point distribution approaches using distance fields. Our new process allows us to produce digital stippling that fills areas with stipple dots without visual artifacts as well as includes clear linear…

Graphics · Computer Science 2023-07-04 Germán Arroyo , Domingo Martín , Tobias Isenberg

We give asymptotic estimates for the mean number of divisors of integers without small prime factors, integers with bounded ratios of consecutive divisors, and for practical numbers. In the last case, this confirms a conjecture of…

Number Theory · Mathematics 2023-06-28 Andreas Weingartner

In this paper, we study the distribution of the minimal distance (in the Hamming metric) of a random linear code of dimension $k$ in $\mathbb{F}_q^n$. We provide quantitative estimates showing that the distribution function of the minimal…

Information Theory · Computer Science 2020-07-15 Jing Hao , Han Huang , Galyna Livshyts , Konstantin Tikhomirov

Applying an original megaideal-based version of the algebraic method, we compute the point-symmetry pseudogroup of the dispersionless (potential symmetric) Nizhnik equation. This is the first example of this kind in the literature, where…

Exactly Solvable and Integrable Systems · Physics 2024-02-27 Vyacheslav M. Boyko , Roman O. Popovych , Oleksandra O. Vinnichenko

Regenerating codes allow distributed storage systems to recover from the loss of a storage node while transmitting the minimum possible amount of data across the network. We present a systematic computer search for optimal systematic…

Information Theory · Computer Science 2009-10-14 Daniel Cullina , Alexandros G. Dimakis , Tracey Ho

A well-known result, due to Meyer, states that the set P of Pisot numbers, generating a real algebraic number field K, is uniformly discrete and relatively dense in the set of positive real number. In the present paper, we show that P is…

Number Theory · Mathematics 2024-02-12 Toufik Zaimi

We estimate optimal thresholds for surface code in the presence of loss via an analytical method developed in statistical physics. The optimal threshold for the surface code is closely related to a special critical point in a…

Quantum Physics · Physics 2015-06-04 Masayuki Ohzeki

We extend coordinate descent to manifold domains, and provide convergence analyses for geodesically convex and non-convex smooth objective functions. Our key insight is to draw an analogy between coordinate blocks in Euclidean space and…

Optimization and Control · Mathematics 2020-06-16 David Huckleberry Gutman , Nam Ho-Nguyen

Recent years have seen renewed attention to arithmetic coding (AC). This is thanks to the use of AC for distribution matching (DM) to control the channel input distribution in probabilistic amplitude shaping. There are two main problems…

Information Theory · Computer Science 2022-08-15 Yunus Can Gültekin , Frans M. J. Willems , Alex Alvarado

Kernel embeddings of distributions and the Maximum Mean Discrepancy (MMD), the resulting distance between distributions, are useful tools for fully nonparametric two-sample testing and learning on distributions. However, it is rarely that…

Machine Learning · Statistics 2017-11-07 Ho Chung Leon Law , Christopher Yau , Dino Sejdinovic

We consider the problem of estimating the locations of a set of points in a k-dimensional euclidean space given a subset of the pairwise distance measurements between the points. We focus on the case when some fraction of these measurements…

Information Theory · Computer Science 2012-10-19 Venkatesan Ekambaram , Giulia Fanti , Kannan Ramchandran

In this paper, we provide some analysis on the asymptotic escape of strict saddles in manifold optimization using the projected gradient descent (PGD) algorithm. One of our main contributions is that we extend the current analysis to…

Optimization and Control · Mathematics 2020-06-30 Thomas Y. Hou , Zhenzhen Li , Ziyun Zhang

We observe that a probability distribution supported by $\mathbb{N}$, induces a representation of real numbers in [0, 1) with digits in $\mathbb{N}$. We first study the Hausdorff dimension of sets with prescribed digits with respect to…

Dynamical Systems · Mathematics 2024-06-18 Jörg Neunhäuserer

The wide availability of biological data at the genome-scale and across multiple variables has resulted in statistical questions regarding the enrichment or depletion of the number of discrete objects (e.g. genes) identified in individual…

Probability · Mathematics 2014-04-21 Alex T. Kalinka

We study the relationship between the frequency of a ternary digit in a number and the asymptotic mean value of the digits. The conditions for the existence of the asymptotic mean of digits in a ternary number are established. We indicate…

Number Theory · Mathematics 2026-03-06 S. O. Klymchuk , O. P. Makarchuk , M. V. Pratsiovytyi

Under the data manifold hypothesis, high-dimensional data are concentrated near a low-dimensional manifold. We study the problem of Riemannian optimization over such manifolds when they are given only implicitly through the data…

Machine Learning · Computer Science 2026-03-03 Andrey Kharitenko , Zebang Shen , Riccardo de Santi , Niao He , Florian Doerfler
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