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Probabilistic models are proposed for bounding the forward error in the numerically computed inner product (dot product, scalar product) between of two real $n$-vectors. We derive probabilistic perturbation bounds, as well as probabilistic…

Numerical Analysis · Mathematics 2019-06-26 Ilse C. F. Ipsen , Hua Zhou

Bayesian methods are often optimal, yet increasing pressure for fast computations, especially with streaming data, brings renewed interest in faster, possibly sub-optimal, solutions. The extent to which these algorithms approximate Bayesian…

Statistics Theory · Mathematics 2026-02-18 Sandra Fortini , Sonia Petrone

We discuss the use of matrices for providing sequences of rationals that approximate algebraic irrationalities. In particular, we study the regular representation of algebraic extensions, proving that ratios between two entries of the…

Number Theory · Mathematics 2020-03-10 Stefano Barbero , Umberto Cerruti , Nadir Murru

This paper presents a synthesis approach aiming to guarantee a minimum upper-bound for the time taken to reach a target set of non-zero measure that encompasses the origin, while taking into account uncertainties and input and state…

Systems and Control · Electrical Eng. & Systems 2026-04-21 Víctor Costa da Silva Campos , Mariella Maia Quadros , Luciano Frezzato , Leonardo Mozelli , Anh-Tu Nguyen

The application of the Gershgorin circle theorem and some of its derivatives to estimate the eigenvalues of a matrix is considered. The obtained results are developed to obtain the localization region of the eigenvalues of a matrix with…

Systems and Control · Electrical Eng. & Systems 2024-09-16 Igor Furtat

We investigate joint spectral characteristics of a family of matrices $\mathcal F $, associated with products in the semigroup generated by $\mathcal F$. In the literature, extremal measures such as the well-known joint spectral radius and…

Dynamical Systems · Mathematics 2026-04-27 Francesco Paolo Maiale , Anastasiia Trofimova , Nicola Guglielmi

We prove a Chernoff-type bound for sums of matrix-valued random variables sampled via a regular (aperiodic and irreducible) finite Markov chain. Specially, consider a random walk on a regular Markov chain and a Hermitian matrix-valued…

Machine Learning · Statistics 2020-10-30 Jiezhong Qiu , Chi Wang , Ben Liao , Richard Peng , Jie Tang

Simple methods permit to generalize the concepts of iteration and of recursive processes. We shall see briefly on several examples what these methods generate. In additive sequences, we shall encounter not only the golden or the silver…

Dynamical Systems · Mathematics 2012-11-20 Andrei Vieru

In the paper I study properties of random polynomials with respect to a general system of functions. Some lower bounds for the mathematical expectation of the uniform and recently introduced integral-uniform norms of random polynomials are…

Probability · Mathematics 2007-05-23 Pavel Grigoriev

This is an expository paper on tensor products where the standard approaches for constructing concrete instances of algebraic tensor products of linear spaces, via quotient spaces or via linear maps of bilinear maps, are reviewed by…

Functional Analysis · Mathematics 2021-08-31 C. S. Kubrusly

This paper proposes a family of weighted batch means variance estimators, which are computationally efficient and can be conveniently applied in practice. The focus is on Markov chain Monte Carlo simulations and estimation of the asymptotic…

Statistics Theory · Mathematics 2018-05-23 Ying Liu , James M. Flegal

Let ${\cal X }=XX^{\prime}$ be a random matrix associated with a centered $r$-column centered Gaussian vector $X$ with a covariance matrix $P$. In this article we compute expectations of matrix-products of the form $\prod_{1\leq i\leq…

Statistics Theory · Mathematics 2017-03-03 Pierre Del Moral , Adrian N. Bishop

Considering a Manhattan mobility model in vehicle-to-vehicle networks, this work studies a power minimization problem subject to second-order statistical constraints on latency and reliability, captured by a network-wide maximal data queue…

Networking and Internet Architecture · Computer Science 2018-10-30 Chen-Feng Liu , Mehdi Bennis

In this paper, we introduce product interactions, an algebraic formalism in which neural network layers are constructed from compositions of a multiplication operator defined over suitable algebras. Product interactions provide a principled…

Machine Learning · Computer Science 2026-02-04 Haonan Dong , Chun-Wun Cheng , Angelica I. Aviles-Rivero

We study detection of random signals corrupted by noise that over time switch their values (states) from a finite set of possible values, where the switchings occur at unknown points in time. We model such signals by means of a random…

Information Theory · Computer Science 2017-12-27 Dragana Bajović , Kanghang He , Lina Stanković , Dejan Vukobratović , Vladimir Stanković

Many scientific applications require the evaluation of the action of the matrix function over a vector and the most common methods for this task are those based on the Krylov subspace. Since the orthogonalization cost and memory requirement…

Numerical Analysis · Mathematics 2026-03-24 Nicolas L. Guidotti , Per-Gunnar Martinsson , Juan A. Acebrón , José Monteiro

In this study, a new extension of the Markov Renewal theory is introduced by allowing time to evolve in multiple dimensions. The resulting chains are referred to as multi-time Markov Renewal chains and since this extension is new, the state…

Probability · Mathematics 2025-08-21 Leonidas Kordalis , Samis Trevezas

Assortment optimization is an important problem that arises in many industries such as retailing and online advertising where the goal is to find a subset of products from a universe of substitutable products which maximize seller's…

Theoretical Economics · Economics 2020-12-15 Kumar Goutam , Vineet Goyal , Agathe Soret

This paper proposes a quantum-classical algorithm to evaluate and select classical artificial neural networks architectures. The proposed algorithm is based on a probabilistic quantum memory and the possibility to train artificial neural…

The exact value of the Lyapunov exponents for the random matrix product $P_N = A_N A_{N-1}...A_1$ with each $A_i = \Sigma^{1/2} G_i^{\rm c}$, where $\Sigma$ is a fixed $d \times d$ positive definite matrix and $G_i^{\rm c}$ a $d \times d$…

Probability · Mathematics 2015-06-16 Peter J. Forrester