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Accurate approximation of probability measures is essential in numerical applications. This paper explores the quantization of probability measures using the maximum mean discrepancy (MMD) distance as a guiding metric. We first investigate…

Optimization and Control · Mathematics 2025-03-18 Zahra Mehraban , Alois Pichler

We study the set M(X) of full non-atomic Borel (finite or infinite) measures on a non-compact locally compact Cantor set X. For an infinite measure $\mu$ in M(X), the set $\mathfrak{M}_\mu = \{x \in X : {for any compact open set} U \ni x…

Dynamical Systems · Mathematics 2012-04-03 O. Karpel

The quantization scheme in probability theory deals with finding a best approximation of a given probability distribution by a probability distribution that is supported on finitely many points. In this paper, first we state and prove a…

Probability · Mathematics 2023-05-05 Juan Gomez , Haily Martinez , Mrinal K. Roychowdhury , Alexis Salazar , Daniel J. Vallez

In this paper we consider the problem of unambiguous discrimination between a set of linearly independent pure quantum states. We show that the design of the optimal measurement that minimizes the probability of an inconclusive result can…

Quantum Physics · Physics 2016-11-17 Yonina C. Eldar

We study experimentally systems of orthogonal polynomials with respect to self-similar measures. When the support of the measure is a Cantor set, we observe some interesting properties of the polynomials, both on the Cantor set and in the…

Classical Analysis and ODEs · Mathematics 2009-10-06 Steven M. Heilman , Philip Owrutsky , Robert S. Strichartz

We describe a measure quantization procedure i.e., an algorithm which finds the best approximation of a target probability law (and more generally signed finite variation measure) by a sum of $Q$ Dirac masses ($Q$ being the quantization…

Machine Learning · Statistics 2024-11-26 Gabriel Turinici

For arbitrary Borel probability measures with compact support on the real line, characterizations are established of the best finitely supported approximations, relative to three familiar probability metrics (Levy, Kantorovich, and…

Probability · Mathematics 2018-03-29 Arno Berger , Chuang Xu

We study the quantization errors for the doubling probability measures $\mu$ which are supported on a class of Moran sets $E\subset\mathbb{R}^q$. For each $n\geq 1$, let $\alpha_n$ be an arbitrary $n$-optimal set for $\mu$ of order $r$ and…

Functional Analysis · Mathematics 2019-08-02 Sanguo Zhu

We show that every homeomorphism between closed measure zero subsets extends to a measure preserving auto-homeomorphism, whenever the Cantor set is endowed with a suitable probability measure. This is valid both for the standard product…

Probability · Mathematics 2021-08-25 W. Bielas , W. Kubiś , M. Walczyńska

We investigate the possibility of defining meaningful upper and lower quantization dimensions for a compactly supported Borel probability measure of order $r$, including negative values of $r$. To this end, we use the concept of partition…

Probability · Mathematics 2026-01-14 Marc Kesseböhmer , Aljoscha Niemann

Given random samples drawn i.i.d. from a probability measure $\mathbb{P}$ (defined on say, $\mathbb{R}^d$), it is well-known that the empirical estimator is an optimal estimator of $\mathbb{P}$ in weak topology but not even a consistent…

Statistics Theory · Mathematics 2016-03-31 Bharath Sriperumbudur

This paper addresses the case where data come as point sets, or more generally as discrete measures. Our motivation is twofold: first we intend to approximate with a compactly supported measure the mean of the measure generating process,…

Statistics Theory · Mathematics 2021-03-19 Frédéric Chazal , Clément Levrard , Martin Royer

Bucklew and Wise (1982) showed that the quantization dimension of an absolutely continuous probability measure on a given Euclidean space is constant and equals the Euclidean dimension of the space, and the quantization coefficient exists…

Probability · Mathematics 2025-07-23 Evans Nyanney , Megha Pandey , Mrinal Kanti Roychowdhury

A method to compute the optimal success probability of discrimination of N arbitrary quantum states is presented, based on the decomposition of any N-outcome measurement into sequences of nested two-outcome ones. In this way the…

Quantum Physics · Physics 2017-04-12 Matteo Rosati , Giacomo De Palma , Andrea Mari , Vittorio Giovannetti

Given a channel having binary input X = (x_1, x_2) having the probability distribution p_X = (p_{x_1}, p_{x_2}) that is corrupted by a continuous noise to produce a continuous output y \in Y = R. For a given conditional distribution…

Signal Processing · Electrical Eng. & Systems 2020-01-13 Thuan Nguyen , Thinh Nguyen

Let $G$ be one of the lamplighter groups $({\mathbb{Z}/p\bz})^n\wr\mathbb{Z}$ and $\Sub(G)$ the space of all subgroups of $G$. We determine the perfect kernel and Cantor-Bendixson rank of $\Sub(G)$. The space of all conjugation-invariant…

Group Theory · Mathematics 2013-09-03 Lewis Bowen , Rostislav Grigorchuk , Rostyslav Kravchenko

We study the quantization for a class of in-homogeneous self-similar measures $\mu$ supported on self-similar sets. Assuming the open set condition for the corresponding iterated function system, we prove the existence of the quantization…

Metric Geometry · Mathematics 2014-07-14 Sanguo Zhu

We study the set $M_\infty(X)$ of all infinite full non-atomic Borel measures on a Cantor space X. For a measure $\mu$ from $M_\infty(X)$ we define a defective set $M_\mu = \{x \in X : for any clopen set U which contains x we have \mu(U) =…

Dynamical Systems · Mathematics 2011-02-08 Olena Karpel

Quantization for probability distributions refers broadly to estimating a given probability measure by a discrete probability measure supported by a finite number of points. We consider general geometric approaches to quantization using…

Dynamical Systems · Mathematics 2020-02-11 Joseph Rosenblatt , Mrinal Kanti Roychowdhury

In this paper, first we have defined a uniform distribution on the boundary of a regular hexagon, and then investigated the optimal sets of $n$-means and the $n$th quantization errors for all positive integers $n$. We give an exact formula…