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We calculate within a semiclassical approximation the autocorrelation function of cross sections. The starting point is the semiclassical expression for the diagonal matrix elements of an operator. For general operators with a smooth…

Chaotic Dynamics · Physics 2007-08-22 Bruno Eckhardt , Shmuel Fishman , Imre Varga

The conventional rounding error analysis provides worst-case bounds with an associated failure probability and ignores the statistical property of the rounding errors. In this paper, we develop a new statistical rounding error analysis for…

Numerical Analysis · Mathematics 2025-11-04 Yiming Fang , Li Chen

We consider exact matrix decomposition by Gauss-Bareiss reduction. We investigate two aspects of the process: common row and column factors and the influence of pivoting strategies. We identify two types of common factors: systematic and…

Symbolic Computation · Computer Science 2016-03-14 Johannes Middeke , David J. Jeffrey

First some old as well as new results about P.I. algebras, Ore extensions, and degrees are presented. Then quantized $n\times r$ matrices as well as quantized factor algebras of $M_q(n)$ are analyzed. The latter are the quantized function…

Quantum Algebra · Mathematics 2007-05-23 Hans Plesner Jakobsen , Søren Jøndrup

In this paper, we concentrate on the backward error and condition number of the indefinite least squares problem. For the normwise backward error of the indefinite least square problem, we adopt the linearization method to derive the tight…

Numerical Analysis · Mathematics 2016-12-21 Huai-An Diao , Tong-Yu Zhou

We present a new filtered low-regularity Fourier integrator for the cubic nonlinear Schr\"odinger equation based on recent time discretization and filtering techniques. For this new scheme, we perform a rigorous error analysis and establish…

Numerical Analysis · Mathematics 2019-02-20 Alexander Ostermann , Frédéric Rousset , Katharina Schratz

We establish two inequalities in real inner product spaces. The first is a multiplicative strengthening of the classical Hornich-Hlawka inequality: for all vectors $x, y, z$ in a real inner product space $H$ \[ \|x\|\,\|y\| +…

Classical Analysis and ODEs · Mathematics 2026-05-12 Nizar El Idrissi , Hicham Zoubeir

The solution to empirical risk minimization with $f$-divergence regularization (ERM-$f$DR) is extended to constrained optimization problems, establishing conditions for equivalence between the solution and constraints. A dual formulation of…

Machine Learning · Statistics 2025-02-21 Francisco Daunas , Iñaki Esnaola , Samir M. Perlaza , Gholamali Aminian

We show that, for a certain class of partitions and an even number of variables of which half are reciprocals of the other half, Schur polynomials can be factorized into products of odd and even orthogonal characters. We also obtain related…

Combinatorics · Mathematics 2019-02-07 Arvind Ayyer , Roger E. Behrend

Matrix factorization is a popular approach for large-scale matrix completion. The optimization formulation based on matrix factorization can be solved very efficiently by standard algorithms in practice. However, due to the non-convexity…

Machine Learning · Computer Science 2016-11-18 Ruoyu Sun , Zhi-Quan Luo

Let there be given a probability measure $\mu$ on the unit circle $\TT$ of the complex plane and consider the inner product induced by $\mu$. In this paper we consider the problem of orthogonalizing a sequence of monomials $\{z^{r_k}\}_k$,…

Classical Analysis and ODEs · Mathematics 2012-12-07 Ruyman Cruz Barroso , Steven Delvaux

We investigate a general matrix factorization for deviance-based data losses, extending the ubiquitous singular value decomposition beyond squared error loss. While similar approaches have been explored before, our method leverages…

Machine Learning · Statistics 2023-07-04 Liang Wang , Luis Carvalho

In estimation of a normal mean matrix under the matrix quadratic loss, we develop a general formula for the matrix quadratic risk of orthogonally invariant estimators. The derivation is based on several formulas for matrix derivatives of…

Statistics Theory · Mathematics 2023-08-07 Takeru Matsuda

The randomly pivoted partial Cholesky algorithm (RPCholesky) computes a factorized rank-k approximation of an N x N positive-semidefinite (psd) matrix. RPCholesky requires only (k + 1) N entry evaluations and O(k^2 N) additional arithmetic…

Numerical Analysis · Mathematics 2024-10-23 Yifan Chen , Ethan N. Epperly , Joel A. Tropp , Robert J. Webber

Let $R$ be a commutative unital ring. A well-known factorization problem is whether any matrix in $\mathrm{SL}_n(R)$ is a product of elementary matrices with entries in $R$. To solve the problem, we use two approaches based on the notion of…

Commutative Algebra · Mathematics 2019-02-12 Evgueni Doubtsov , Frank Kutzschebauch

In this paper, we describe the randomized QLP (RQLP) algorithm and its enhanced version (ERQLP) for computing the low rank approximation to $A$ of size $m\times n$ efficiently such that $A\approx QLP$, where $L$ is the rank-$k$…

Numerical Analysis · Mathematics 2018-11-26 Nianci Wu , Hua Xiang

The paper revisits the classical problem of evaluating $f(A)$ for a real function $f$ and a matrix $A$ with real spectrum. The evaluation is based on expanding $f$ in Chebyshev polynomials, and the focus of the paper is to study the…

Numerical Analysis · Mathematics 2018-12-27 Nir Sharon , Yoel Shkolnisky

For a function $W\in \mathbb{C}[X]$ on a smooth algebraic variety $X$ with Morse-Bott critical locus $Y\subset X$, Kapustin, Rozansky and Saulina suggest that the associated matrix factorisation category $\mathrm{MF}(X;W)$ should be…

Algebraic Geometry · Mathematics 2020-03-18 Constantin Teleman

We study categories of matrix factorizations. These categories are defined for any regular function on a suitable regular scheme. Our paper has two parts. In the first part we develop the foundations; for example we discuss derived direct…

Algebraic Geometry · Mathematics 2013-10-25 Valery A. Lunts , Olaf M. Schnürer

We propose and analyze a randomized two-sided Gram-Schmidt process for the biorthogonalization of two given matrices $X, Y \in\mathbb{R}^{n\times m}$. The algorithm aims to find two matrices $Q, P \in\mathbb{R}^{n\times m}$ such that ${\rm…

Numerical Analysis · Mathematics 2025-09-05 Laura Grigori , Lorenzo Piccinini , Igor Simunec