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We introduce and study invariant (weighted) transport-kernels balancing stationary random measures on a locally compact Abelian group. The first main result is an associated fundamental invariance property of Palm measures, derived from a…

Probability · Mathematics 2009-06-12 Günter Last , Hermann Thorisson

We study ergodic properties of a family of traffic maps acting in the space of bi-infinite sequences of real numbers. The corresponding dynamics mimics the motion of vehicles in a simple traffic flow, which explains the name. Using…

Dynamical Systems · Mathematics 2015-06-11 Michael Blank

We consider invariant transports of stationary random measures on $\mathbb{R}^d$ and establish natural mixing criteria that guarantee persistence of asymptotic variances. To check our mixing assumptions, which are based on two-point Palm…

Probability · Mathematics 2025-06-09 Michael A. Klatt , Günter Last , Luca Lotz , D. Yogeshwaran

We develop a theory of optimal transport for stationary random measures with a focus on stationary point processes and construct a family of distances on the set of stationary random measures. These induce a natural notion of interpolation…

Probability · Mathematics 2024-02-02 Matthias Erbar , Martin Huesmann , Jonas Jalowy , Bastian Müller

Motivated by problems of statistical language modeling, we consider probability measures on infinite sequences over two countable alphabets of a different cardinality, such as letters and words. We introduce an invertible mapping between…

Probability · Mathematics 2025-05-27 Łukasz Dębowski

We consider a lcsc group G acting properly on a Borel space S and measurably on an underlying sigma-finite measure space. Our first main result is a transport formula connecting the Palm pairs of jointly stationary random measures on S. A…

Probability · Mathematics 2010-09-22 Daniel Gentner , Günter Last

We investigate stability of invariant measures of diffusion processes with respect to $L^p$ distances on the coefficients, under an assumption of log-concavity. The method is a variant of a technique introduced by Crippa and De Lellis to…

Probability · Mathematics 2020-10-28 Max Fathi , Dan Mikulincer

In this work, we show that for all statistical estimation problems, a natural MMSE instability (discontinuity) condition implies the failure of stable algorithms, serving as a version of OGP for estimation tasks. Using this criterion, we…

Statistics Theory · Mathematics 2026-03-24 Xifan Yu , Ilias Zadik

Mass-stationarity means that the origin is at a typical location in the mass of a random measure. It is an intrinsic characterisation of Palm versions with respect to stationary random measures. Stationarity is the special case when the…

Probability · Mathematics 2015-07-20 Guenter Last , Hermann Thorisson

Kernel based methods provide a way to reconstruct potentially high-dimensional functions from meshfree samples, i.e., sampling points and corresponding target values. A crucial ingredient for this to be successful is the distribution of the…

Numerical Analysis · Mathematics 2021-05-19 Tizian Wenzel , Gabriele Santin , Bernard Haasdonk

In graph analysis, a classic task consists in computing similarity measures between (groups of) nodes. In latent space random graphs, nodes are associated to unknown latent variables. One may then seek to compute distances directly in the…

Machine Learning · Statistics 2022-01-12 Nicolas Keriven

Here we present an ergodic theorem which adapts a Theorem by J. Elton to the classical thermodynamical formalism and to ergodic transport. First, we discuss how Elton's theorem can be used to characterise Gibbs measures for expanding maps.…

Dynamical Systems · Mathematics 2019-02-22 Joana Mohr , Rafael Rigão Souza

A novel algorithm is proposed to solve the sample-based optimal transport problem. An adversarial formulation of the push-forward condition uses a test function built as a convolution between an adaptive kernel and an evolving probability…

Machine Learning · Statistics 2020-06-11 Daeyoung Kim , Esteban G. Tabak

We revisit processes generated by iterated random functions driven by a stationary and ergodic sequence. Such a process is called strongly stable if a random initialization exists, for which the process is stationary and ergodic, and for…

Probability · Mathematics 2024-02-06 László Györfi , Attila Lovas , Miklós Rásonyi

We generalize various notions of stability of invariant sets of dynamical systems to invariant measures, by defining a topology on the set of measures. The defined topology is similar, but not topologically equivalent to weak* topology, and…

Dynamical Systems · Mathematics 2008-11-04 Sinisa Slijepcevic

Random metastability occurs when an externally forced or noisy system possesses more than one state of apparent equilibrium. This work investigates a class of random dynamical systems, arising from perturbing a one-dimensional piecewise…

Dynamical Systems · Mathematics 2025-10-27 Cecilia González-Tokman , Joshua Peters

In this paper, we consider the communication complexity of protocols that compute stable matchings. We work within the context of Gale and Shapley's original stable marriage problem\cite{GS62}: $n$ men and $n$ women each privately hold a…

Computational Complexity · Computer Science 2014-10-10 Rafail Ostrovsky , Will Rosenbaum

In this paper, we are concerned with estimating the joint probability of random variables $X$ and $Y$, given $N$ independent observation blocks $(\boldsymbol{x}^i,\boldsymbol{y}^i)$, $i=1,\ldots,N$, each of $M$ samples…

Machine Learning · Statistics 2024-02-14 Florian Beier , Hancheng Bi , Clément Sarrazin , Bernhard Schmitzer , Gabriele Steidl

We establish a general form of explicit, input-dependent, measure-valued warpings for learning nonstationary kernels. While stationary kernels are ubiquitous and simple to use, they struggle to adapt to functions that vary in smoothness…

Machine Learning · Computer Science 2020-10-12 Anthony Tompkins , Rafael Oliveira , Fabio Ramos

We study a stability property of probability laws with respect to small violations of algorithmic randomness. A sufficient condition of stability is presented in terms of Schnorr tests of algorithmic randomness. Most probability laws, like…

Computational Complexity · Computer Science 2014-09-16 Vladimir V. V'yugin
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