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We introduce the notion of dynamical metric order of a continuous map on a compact metric space, study its basic properties, and compute it for several classes of maps. This concept which is a counterpart of the metric mean dimension with…

Dynamical Systems · Mathematics 2026-04-14 Maria Carvalho , Fagner B. Rodrigues

Bayesian optimization (BO) is a popular technique for sequential black-box function optimization, with applications including parameter tuning, robotics, environmental monitoring, and more. One of the most important challenges in BO is the…

Machine Learning · Computer Science 2018-03-29 Paul Rolland , Jonathan Scarlett , Ilija Bogunovic , Volkan Cevher

One of the goals of this article is to define a an unified setting adapted to the description of means (normalized integrals or invariant means) on an infinite product of measured spaces with infinite measure. We first remark that some…

Differential Geometry · Mathematics 2018-07-16 Jean-Pierre Magnot

The merit of projecting data onto linear subspaces is well known from, e.g., dimension reduction. One key aspect of subspace projections, the maximum preservation of variance (principal component analysis), has been thoroughly researched…

Machine Learning · Computer Science 2022-09-27 Erik Thordsen , Erich Schubert

Metric mean dimension is a metric-depedent quantity to characterize the topological complexity of systems with infinite topological entropy. In this paper, we investigate metric mean dimension of factor maps. (1) We introduce three types of…

Dynamical Systems · Mathematics 2026-05-19 Rui Yang

We generalize the concept of mutually unbiased bases (MUB) to measurements which are not necessarily described by rank one projectors. As such, these measurements can be a useful tool to study the long standing problem of the existence of…

Quantum Physics · Physics 2015-06-18 Amir Kalev , Gilad Gour

This chapter presents key concepts and theoretical results for analyzing estimation and inference in high-dimensional models. High-dimensional models are characterized by having a number of unknown parameters that is not vanishingly small…

Statistics Theory · Mathematics 2018-06-12 Alexandre Belloni , Victor Chernozhukov , Denis Chetverikov , Christian Hansen , Kengo Kato

We introduce the notions of in-betweenness and monotonicity with respect to a metric, for operator means. These notions can be seen as generalising their natural counterpart for scalar means, and as a relaxation of the notion of geodesity.…

Functional Analysis · Mathematics 2013-04-23 Koenraad M. R. Audenaert

We study a new hyperbolic type metric recently introduced by Song and Wang. We present formulas for it in the upper half-space and the unit ball domains and find its sharp inequalities with the hyperbolic metric and the triangular ratio…

Metric Geometry · Mathematics 2024-06-26 Oona Rainio

Spherical means are well-known useful tool in the theory of partial differential equations with applications to solving hyperbolic and ultrahyperbolic equations and problems of integral geometry, tomography and Radon transforms. We…

Classical Analysis and ODEs · Mathematics 2016-10-17 E. L. Shishkina , S. M. Sitnik

We introduce the notion of coarse metric. Every coarse metric induces a coarse structure on the underlying set. Conversely, we observe that all coarse spaces come from a particular type of coarse metric in a unique way. In the case when the…

Metric Geometry · Mathematics 2020-12-15 Chi-Keung Ng

In this article, using the generalized Newton transformation, we define higher order mean curvatures of distributions of arbitrary codimension and we show that they agree with the ones from Brito and Naveira (Ann. Global Anal. Geom. 18,…

Differential Geometry · Mathematics 2013-06-14 Krzysztof Andrzejewski , Pawel Walczak

It is well-known that the relativized variational principle established by Bogenschutz and Kifer connects the fiber topological entropy and fiber measure-theoretic entropy. In context of random dynamical systems, metric mean dimension was…

Dynamical Systems · Mathematics 2025-09-24 Yunping Wang , Ercai Chen , Kexiang Yang

A new type of differential equations for probability measures on Euclidean spaces, called Measure Differential Equations (briefly MDEs), is introduced. MDEs correspond to Probability Vector Fields, which map measures on an Euclidean space…

Optimization and Control · Mathematics 2017-09-01 Benedetto Piccoli

The aim of this article is to make a contribution to the Bayesian procedure of testing precise hypotheses for parametric models. For this purpose, we define the Bayesian Discrepancy Measure that allows one to evaluate the suitability of a…

Methodology · Statistics 2022-11-21 Francesco Bertolino , Mara Manca , Monica Musio , Walter Racugno , Laura Ventura

The aim of this paper is to discuss both higher-order asymptotic expansions and skewed approximations for the Bayesian Discrepancy Measure for testing precise statistical hypotheses. In particular, we derive results on third-order…

Methodology · Statistics 2025-05-02 Elena Bortolato , Francesco Bertolino , Monica Musio , Laura Ventura

Infinite sets of inequalities which generalize all the known inequalities that can be used in the majorization step of the Approximating Hamiltonian method are derived. They provide upper bounds on the difference between the quadratic…

Mathematical Physics · Physics 2011-06-20 J. G. Brankov , N. S. Tonchev

We introduce the notion of Feldman-Katok metric mean dimensions in this note. We show metric mean dimensions defined by different metrics coincide under weak tame growth of covering numbers, and establish variational principles for…

Dynamical Systems · Mathematics 2023-10-11 Yunxiang Xie , Ercai Chen , Rui Yang

In this paper we extend the definitions of mean dimension and metric mean di-mension for non-autonomous dynamical systems. We show some properties of this extension and furthermore some applications to the mean dimension and metric mean…

Dynamical Systems · Mathematics 2021-04-02 Fagner Bernardini Rodrigues , Jeovanny de Jesus Muentes Acevedo

A stochastic PDE, describing mesoscopic fluctuations in systems of weakly interacting inertial particles of finite volume, is proposed and analysed in any finite dimension $d\in\mathbb{N}$. It is a regularised and inertial version of the…

Analysis of PDEs · Mathematics 2021-02-10 Federico Cornalba , Tony Shardlow , Johannes Zimmer
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