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We establish integral tests and laws of the iterated logarithm for the lower envelope of positive self-similar Markov processes at 0 and $+\infty$. Our proofs are based on the Lamperti representation and time reversal arguments. These…

Probability · Mathematics 2016-08-16 Loïc Chaumont , Juan-Carlos Pardo

We introduce the notion of a combinatorial inverse system in non-commutative variables. We present two important examples, some conjectures and results. These conjectures and results were suggested and supported by computer investigations.

Rings and Algebras · Mathematics 2010-10-05 J. -C. Aval , N. Bergeron , H. Li

In this paper we study a family of nonlinear (conditional) expectations that can be understood as a semimartingale with uncertain local characteristics. Here, the differential characteristics are prescribed by a time and path-dependent…

Probability · Mathematics 2023-11-07 David Criens , Lars Niemann

We consider a multivariate L\'evy process where the first coordinate is a L\'evy process with no negative jumps which is not a subordinator and the others are nondecreasing. We determine the Laplace-Stieltjes transform of the steady-state…

Probability · Mathematics 2020-11-25 Offer Kella , Onno Boxma

Since data is the fuel that drives machine learning models, and access to labeled data is generally expensive, semi-supervised methods are constantly popular. They enable the acquisition of large datasets without the need for too many…

Machine Learning · Computer Science 2023-01-12 Jędrzej Kozal , Michał Woźniak

Levy processes, which have stationary independent increments, are ideal for modelling the various types of noise that can arise in communication channels. If a Levy process admits exponential moments, then there exists a parametric family…

Probability · Mathematics 2019-05-02 Dorje C. Brody , Lane P. Hughston , Xun Yang

We propose an l1-regularized likelihood method for estimating the inverse covariance matrix in the high-dimensional multivariate normal model in presence of missing data. Our method is based on the assumption that the data are missing at…

Methodology · Statistics 2012-02-28 Nicolas Städler , Peter Bühlmann

An algorithm for finding the eigenvalue of a nonnegative irreducible tensor was recently proposed by Michael Ng, Liqun Qi, and Guanglu Zhou in {\it Finding the largest eigenvalue of a nonnegative tensor}. However, the authors did not prove…

Numerical Analysis · Mathematics 2010-11-19 K. J. Pearson

In this paper we present some extensions of recent noncentral moderate deviation results in the literature. In the first part we generalize the results in \cite{BeghinMacciSPL2022} by considering a general L\'evy process $\{S(t):t\geq 0\}$…

Probability · Mathematics 2025-01-03 Antonella Iuliano , Claudio Macci , Alessandra Meoli

The Lie algebra of vector fields on $R^m$ acts naturally on the spaces of differential operators between tensor field modules. Its projective subalgebra is isomorphic to $sl_{m+1}$, and its affine subalgebra is a maximal parabolic…

Representation Theory · Mathematics 2017-07-31 Charles H. Conley , Dimitar Grantcharov

L\'evy processes on bialgebras are families of infinitely divisible representations. We classify the generators of L\'evy processes on the compact forms of the quantum algebras $U_q(g)$, where $g$ is a simple Lie algebra. Then we show how…

Probability · Mathematics 2007-05-23 V. K. Dobrev , H. -D. Doebner , U. Franz , R. Schott

We introduce a novel Pseudo-Negative Regularization (PNR) framework for effective continual self-supervised learning (CSSL). Our PNR leverages pseudo-negatives obtained through model-based augmentation in a way that newly learned…

Machine Learning · Computer Science 2024-06-10 Sungmin Cha , Kyunghyun Cho , Taesup Moon

Let $X, X_1, X_2,...$ be a sequence of non-degenerate i.i.d. random variables with mean zero. The best possible weighted approximations are investigated in $D[0, 1]$ for the partial sum processes $\{S_{[nt]}, 0\le t\le 1\}$, where…

Probability · Mathematics 2007-11-12 Miklós Csörgő , Barbara Szyszkowicz , Qiying Wang

We characterize all multi-dimensional real self-similar Gaussian Markov processes. Three types of covariance matrix functions occur: white-noise type functions, covariances that can be expressed by continuous matrix semigroups, and…

Probability · Mathematics 2025-08-13 Benedict Bauer , Stefan Gerhold

In several domains obtaining class annotations is expensive while at the same time unlabelled data are abundant. While most semi-supervised approaches enforce restrictive assumptions on the data distribution, recent work has managed to…

Machine Learning · Statistics 2017-10-11 Martin Trapp , Tamas Madl , Robert Peharz , Franz Pernkopf , Robert Trappl

We introduce a novel semi-supervised version of the least squares classifier. This implicitly constrained least squares (ICLS) classifier minimizes the squared loss on the labeled data among the set of parameters implied by all possible…

Machine Learning · Statistics 2015-07-27 Jesse H. Krijthe , Marco Loog

A classification of the semisimple subalgebras of the Lie algebra of traceless $3\times 3$ matrices with complex entries, denoted $A_2$, is well-known. We classify its nonsemisimple subalgebras, thus completing the classification of the…

Rings and Algebras · Mathematics 2024-08-20 Andrew Douglas , Joe Repka

For a nonsingular real algebraic curve in the 3-dimensional projective space and sphere a new numeric characteristic is introduced. It takes integer values, is invariant under rigid isotopy, multiplied by -1 under mirror reflection. In a…

alg-geom · Mathematics 2008-02-03 Oleg Viro

A sequential piecewise linear programming method is presented where bounded domains of non-convex functions are successively contracted about the solution of a piecewise linear program at each iteration of the algorithm. Although…

Optimization and Control · Mathematics 2020-04-21 James P. L. Tan

Labeled data used for training activity recognition classifiers are usually limited in terms of size and diversity. Thus, the learned model may not generalize well when used in real-world use cases. Semi-supervised learning augments labeled…

Machine Learning · Computer Science 2018-01-25 Ming Zeng , Tong Yu , Xiao Wang , Le T. Nguyen , Ole J. Mengshoel , Ian Lane
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