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We study optimal solutions to an abstract optimization problem for measures, which is a generalization of classical variational problems in information theory and statistical physics. In the classical problems, information and relative…

Optimization and Control · Mathematics 2021-11-23 Roman V. Belavkin

We obtain a representation of an inhomogeneous Levy process in a Lie group or a homogeneous space in terms of a drift, a matrix function and a measure function. Because the stochastic continuity is not assumed, our result generalizes the…

Probability · Mathematics 2014-12-30 Ming Liao

We study recurrence and transience for L\'{e}vy processes induced by topological transformation groups. In particular the transience-recurrence dichotomy in terms of potential measures is established and transience is shown to be equivalent…

Probability · Mathematics 2011-03-22 David Applebaum

We consider the regularity of sample paths of Volterra-L\'{e}vy processes. These processes are defined as stochastic integrals $$ M(t)=\int_{0}^{t}F(t,r)dX(r), \ \ t \in \mathds{R}_{+}, $$ where $X$ is a L\'{e}vy process and $F$ is a…

Probability · Mathematics 2014-05-20 Eyal Neuman

We describe and analyze a simple random feature scheme (RFS) from prescribed compositional kernels. The compositional kernels we use are inspired by the structure of convolutional neural networks and kernels. The resulting scheme yields…

Machine Learning · Computer Science 2017-03-24 Amit Daniely , Roy Frostig , Vineet Gupta , Yoram Singer

The main result of this paper is that determinantal point processes on the real line corresponding to projection operators with integrable kernels are quasi-invariant, in the continuous case, under the group of diffeomorphisms with compact…

Probability · Mathematics 2016-12-01 Alexander I. Bufetov

In this article we study the structure of $\Gamma$-invariant spaces of $L^2(\bf R)$. Here $\bf R$ is a second countable LCA group. The invariance is with respect to the action of $\Gamma$, a non commutative group in the form of a semidirect…

Functional Analysis · Mathematics 2020-06-15 Davide Barbieri , Carlos Cabrelli , Eugenio Hernández , Ursula Molter

The main result of this paper, Theorem 1.5, establishes a conjecture of Lyons and Peres: for a determinantal point process governed by a reproducing kernel, the system of kernels sampled at the particles of a random configuration is…

Probability · Mathematics 2018-12-19 Alexander I. Bufetov , Yanqi Qiu , Alexander Shamov

Invariance properties of semimartingales on Lie groups under a family of random transformations are defined and investigated, generalizing the random rotations of the Brownian motion. A necessary and sufficient explicit condition…

Probability · Mathematics 2018-12-31 Sergio Albeverio , Francesco C. De Vecchi , Paola Morando , Stefania Ugolini

In the first part of this article, we prove two-sided estimates of hitting probabilities of balls, the potential kernel and the Green function for a ball for general isotropic unimodal L\'evy processes. Our bounds are sharp under the…

Probability · Mathematics 2017-05-24 Tomasz Grzywny , Mateusz Kwaśnicki

The purpose of this article is to develop a theory behind the occurrence of "path-integral" kernels in the study of extended determinantal point processes and non-intersecting line ensembles. Our first result shows how determinants…

Probability · Mathematics 2020-10-15 Alexei Borodin , Ivan Corwin , Daniel Remenik

Determinantal point processes are point processes whose correlation functions are given by determinants of matrices. The entries of these matrices are given by one fixed function of two variables, which is called the kernel of the point…

Classical Analysis and ODEs · Mathematics 2019-06-27 Marco Stevens

We consider a recurrent Markov process which is an It\^o semi-martingale. The L\'evy kernel describes the law of its jumps. Based on observations X(0),X({\Delta}),...,X(n{\Delta}), we construct an estimator for the L\'evy kernel's density.…

Statistics Theory · Mathematics 2013-05-14 Florian A. J. Ueltzhöfer

In this paper we consider the existence of weakly c\`adl\`ag versions of a solution to a linear equation in a Hilbert space $H$, driven by a Levy process taking values in a Hilbert space $U$. In particular we are interested in diagonal type…

Probability · Mathematics 2020-08-17 Witold Bednorz , Anna Talarczyk

In this paper, we show that a suitably chosen covariance function of a continuous time, second order stationary stochastic process can be viewed as a symmetric higher order kernel. This leads to the construction of a higher order kernel by…

Statistics Theory · Mathematics 2020-01-22 Soumya Das , Subhajit Dutta , Radhenduhska Srivastava

Let $\mathbb{R}^N_+= [0,\infty)^N$. We here consider a class of random fields $(X_t)_{t\in \mathbb{R}^N_+}$ which are known as Multiparameter L\'evy processes. Related multiparameter semigroups of operators and their generators are…

Probability · Mathematics 2023-05-31 Francesco Iafrate , Costantino Ricciuti

The one dimensional distribution of a L\'{e}vy process is not known in general even though its characteristic function is given by the famous L\'{e}vy-Khinchine theorem. This article gives an exact series representation for the one…

Probability · Mathematics 2008-09-15 Heikki J. Tikanmäki

The concept of a L\'evy subordinator is generalized to a family of non-decreasing stochastic processes, which are parameterized in terms of two Bernstein functions. Whereas the independent increments property is only maintained in the…

Probability · Mathematics 2019-09-10 Jan-Frederik Mai , Matthias Scherer

For any arbitrary algebraic curve, we define an infinite sequence of invariants. We study their properties, in particular their variation under a variation of the curve, and their modular properties. We also study their limits when the…

Mathematical Physics · Physics 2007-05-23 Bertrand Eynard , Nicolas Orantin

We analyze in this paper a random feature map based on a theory of invariance I-theory introduced recently. More specifically, a group invariant signal signature is obtained through cumulative distributions of group transformed random…

Machine Learning · Computer Science 2015-12-07 Youssef Mroueh , Stephen Voinea , Tomaso Poggio