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We obtain an intertwining relation between some Riemann-Liouville operators of order a in (1,2) connecting through a certain multiplicative identity in law the one-dimensional marginals of reflected completely asymmetric a-stable L\'evy…

Probability · Mathematics 2022-05-24 Pierre Patie , Thomas Simon

Inspired by the commutator and anticommutator algebras derived from algebras graded by groups, we introduce noncommutatively graded algebras. We generalize various classical graded results to the noncommutatively graded situation concerning…

Rings and Algebras · Mathematics 2017-11-01 Patrik Nystedt

Often in applications such as rare events estimation or optimal control it is required that one calculates the principal eigen-function and eigen-value of a non-negative integral kernel. Except in the finite-dimensional case, usually…

Computation · Statistics 2016-09-28 Nick Whiteley , Nikolas Kantas

In this article, we introduce Mittag-Leffler L\'evy process and provide two alternative representations of this process. First, in terms of Laplace transform of the marginal densities and next as a subordinated stochastic process. Both…

Probability · Mathematics 2016-02-05 Arun Kumar , N. S. Upadhye

Let {X_{t_1,t_2}: t_1,t_2 >= 0} be a two-parameter L\'evy process on R^d. We study basic properties of the one-parameter process {X_{x(t),y(t)}: t \in T} where x and y are, respectively, nondecreasing and nonincreasing nonnegative…

Probability · Mathematics 2010-01-08 Shai Covo

Levy processes are widely used in financial mathematics, telecommunication, economics, queueing theory and natural sciences for modelling. A typical model is obtained by considering finite dimensional linear stochastic SISO systems driven…

Statistics Theory · Mathematics 2014-01-07 Laszlo Gerencser , Mate Manfay

Infinite-dimensional Lie algebras are introduced, which are only partially graded, and are specified by indices lying on cyclotomic rings. They may be thought of as generalizations of the Onsager algebra, but unlike it, or its sl(n)…

High Energy Physics - Theory · Physics 2009-10-02 David Fairlie , Cosmas Zachos

In this paper, we propose a novel active learning approach integrated with an improved semi-supervised learning framework to reduce the cost of manual annotation and enhance model performance. Our proposed approach effectively leverages…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Wanli Ma , Oktay Karakus , Paul L. Rosin

Pseudoinverses are ubiquitous tools for handling over- and under-determined systems of equations. For computational efficiency, sparse pseudoinverses are desirable. Recently, sparse left and right pseudoinverses were introduced, using…

Numerical Analysis · Mathematics 2016-06-23 Victor K. Fuentes , Marcia Fampa , Jon Lee

Construction of splitting-step methods and properties of related non-negativity and boundary preserving numerical algorithms for solving stochastic differential equations (SDEs) of Ito-type are discussed. We present convergence proofs for a…

Numerical Analysis · Mathematics 2007-05-23 Esteban Moro , Henri Schurz

We study the spectral properties of a stochastic process obtained by multiplicative inversion of a non-zero-mean Gaussian process. We show that its autocorrelation and power spectrum exist for most regular processes, and we find a…

Statistics Theory · Mathematics 2025-09-16 Marco Lanucara

The aim of this work is to present the description up to isomorphism of Leibniz superalgebras with characteristic sequence (n | m-1, 1) and nilindex n+m.

Rings and Algebras · Mathematics 2008-11-24 L. M. Camacho , J. R. Gómez , R. M. Navarro , B. A. Omirov

Unlike matrix completion, tensor completion does not have an algorithm that is known to achieve the information-theoretic sample complexity rate. This paper develops a new algorithm for the special case of completion for nonnegative…

Machine Learning · Computer Science 2022-05-25 Caleb Bugg , Chen Chen , Anil Aswani

Kuznetsov et al. (2011) and Kuznetsov and Pardo (2013) introduced the family of Hypergeometric L\'evy processes. They appear naturally in the study of fluctuations of stable processes when one analyses stable processes through the theory of…

Probability · Mathematics 2015-09-09 Emma L. Horton , Andreas E. Kyprianou

In this paper we describe the mathematical foundations of a new approach to semi-supervised Machine Learning. Using techniques of Symbolic Computation and Computer Algebra, we apply the concept of persistent homology to obtain a new…

Machine Learning · Computer Science 2023-01-30 Adrián Inés , César Domínguez , Jónathan Heras , Gadea Mata , Julio Rubio

Let $X_1,...,X_N$ denote $N$ independent $d$-dimensional L\'evy processes, and consider the $N$-parameter random field \[\X(\bm{t}):= X_1(t_1)+...+X_N(t_N).\] First we demonstrate that for all nonrandom Borel sets $F\subseteq\R^d$, the…

Probability · Mathematics 2007-06-29 Davar Khoshnevisan , Yimin Xiao

The purpose of these notes is to distribute, mostly without proofs, fundamental definitions and results concerning the theory of semimartingales and stochastic integration. The material serves as a foundational guide for those interested in…

Probability · Mathematics 2025-01-03 Mark van den Bosch

In our today's information society more and more data emerges, e.g.~in social networks, technical applications, or business applications. Companies try to commercialize these data using data mining or machine learning methods. For this…

Machine Learning · Statistics 2016-10-17 Tobias Reitmaier , Adrian Calma , Bernhard Sick

In this article we are interested for the numerical study of nonlinear eigenvalue problems. We begin with a review of theoretical results obtained by functional analysis methods, especially for the Schrodinger pencils. Some recall are given…

Numerical Analysis · Mathematics 2016-08-24 Fatima Aboud , Francois Jauberteau , Guy Moebs , Didier Robert

Semi-supervised learning (SSL) constructs classifiers using both labelled and unlabelled data. It leverages information from labelled samples, whose acquisition is often costly or labour-intensive, together with unlabelled data to enhance…

Machine Learning · Statistics 2025-12-29 Jinran Wu , You-Gan Wang , Geoffrey J. McLachlan