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Similarity functions measure how comparable pairs of elements are, and play a key role in a wide variety of applications, e.g., notions of Individual Fairness abiding by the seminal paradigm of Dwork et al., as well as Clustering problems.…

Machine Learning · Computer Science 2023-10-24 Leonidas Tsepenekas , Ivan Brugere , Freddy Lecue , Daniele Magazzeni

The distribution function of a random distance in three dimensions is given and some new three-dimensional d2-tests of randomness are suggested. We show that our test statistics are not correlated with the usual test statistics and are…

Applications · Statistics 2014-02-24 Sergii Koliada

For two causal structures with the same set of visible variables, one is said to observationally dominate the other if the set of distributions over the visible variables realizable by the first contains the set of distributions over the…

Machine Learning · Statistics 2025-02-24 Marina Maciel Ansanelli , Elie Wolfe , Robert W. Spekkens

In this report, the explicit probability density functions of the random Euclidean distances associated with equilateral triangles are given, when the two endpoints of a link are randomly distributed in 1) the same triangle, 2) two adjacent…

General Mathematics · Mathematics 2013-07-04 Yanyan Zhuang , Jianping Pan

In a recent paper, Aldous, Blanc and Curien asked which distributions can be expressed as the distance between two independent random variables on some separable measured metric space. We show that every nonnegative discrete distribution…

Probability · Mathematics 2025-07-22 Renan Gross

A quasi-infinitely divisible distribution on $\mathbb{R}^d$ is a probability distribution $\mu$ on $\mathbb{R}^d$ whose characteristic function can be written as the quotient of the characteristic functions of two infinitely divisible…

Probability · Mathematics 2021-01-08 David Berger , Merve Kutlu , Alexander Lindner

The first order loss function and its complementary function are extensively used in practical settings. When the random variable of interest is normally distributed, the first order loss function can be easily expressed in terms of the…

Optimization and Control · Mathematics 2014-09-09 Roberto Rossi , S. Armagan Tarim , Steven Prestwich , Brahim Hnich

A class of signed joint probability measures for n arbitrary quantum observables is derived and studied based on quasi-characteristic functions with symmetrized operator orderings of Margenau-Hill type. It is shown that the Wigner…

Quantum Physics · Physics 2024-10-01 Ralph Sabbagh , Olga Movilla Miangolarra , Hamid Hezari , Tryphon T. Georgiou

We propose a class of semimetrics for preference relations any one of which is an alternative to the classical Kemeny-Snell-Bogart metric. (We take a fairly general viewpoint about what constitutes a preference relation, allowing for any…

Combinatorics · Mathematics 2022-03-10 Hiroki Nishimura , Efe A. Ok

For a class of integral operators with kernels metric functions on manifold we find some necessary and sufficient conditions to have finite rank. The problem we pose has a stochastic nature and boils down to the following alternative…

Metric Geometry · Mathematics 2009-04-24 Nikolay H. Balov

We employ the operational quasiprobability (OQ) as a work distribution, which reproduces the Jarzynski equality and yields the average work consistent with the classical definition. The OQ distribution can be experimentally implemented…

Quantum Physics · Physics 2025-10-07 Jeongwoo Jae , Junghee Ryu , Hoon Ryu

To unequivocally distinguish genuine quantumness from classicality, a widely adopted approach focuses on the negative values of a quasi-distribution representation as compelling evidence of nonclassicality. Prominent examples include the…

Quantum Physics · Physics 2024-11-18 Hong-Bin Chen , Cheng-Hua Liu , Kuan-Lun Lai , Bor-Yann Tseng , Ping-Yuan Lo , Yueh-Nan Chen , Chi-Hua Yu

This paper proposes a new method for determining similarity and anomalies between time series, most practically effective in large collections of (likely related) time series, by measuring distances between structural breaks within such a…

Machine Learning · Computer Science 2020-12-01 Nick James , Max Menzies , Lamiae Azizi , Jennifer Chan

We present a novel family of nonparametric omnibus tests of the hypothesis that two unknown but estimable functions are equal in distribution when applied to the observed data structure. We developed these tests, which represent a…

Statistics Theory · Mathematics 2017-06-15 Alexander R. Luedtke , Marco Carone , Mark J. van der Laan

In this paper we consider a fragment of the first-order theory of the real numbers that includes systems of equations of continuous functions in bounded domains, and for which all functions are computable in the sense that it is possible to…

Computational Complexity · Computer Science 2016-08-15 Peter Franek , Stefan Ratschan , Piotr Zgliczynski

In this article we introduce a quasiprobability distribution of work that is based on the Wigner function. This construction rests on the idea that the work done on an isolated system can be coherently measured by coupling the system to a…

Quantum Physics · Physics 2023-11-03 Federico Cerisola , Franco Mayo , Augusto J. Roncaglia

This paper studies the properties of a new lower bound for the natural pseudo-distance. The natural pseudo-distance is a dissimilarity measure between shapes, where a shape is viewed as a topological space endowed with a real-valued…

Computational Geometry · Computer Science 2008-04-23 M. d'Amico , P. Frosini , C. Landi

In recent studies, Bibiloni-Femenias, Mi\~{n}ana and Valero characterized the functions that aggregate a family of (quasi-)(pseudo)metric modulars defined over a fixed set $X$ into a single one. In this paper, we adopt a related but…

General Topology · Mathematics 2025-04-01 Alejandro Fructuoso-Bonet , Jesús Rodríguez-López

Comparing probability distributions is a core challenge across the natural, social, and computational sciences. Existing methods, such as Maximum Mean Discrepancy (MMD), struggle in high-dimensional and non-compact domains. Here we…

Machine Learning · Statistics 2025-09-09 Logan S. McCarty

We propose a revised definition of quasi-distributions within the framework of large-momentum effective theory (LaMET) that improves convergence towards the large-momentum limit. Since the definition of quasi-distributions is not unique,…

High Energy Physics - Phenomenology · Physics 2019-05-13 Tomomi Ishikawa , Luchang Jin , Huey-Wen Lin , Andreas Schäfer , Yi-Bo Yang , Jian-Hui Zhang , Yong Zhao