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We design a new algorithm for solving parametric systems having finitely many complex solutions for generic values of the parameters. More precisely, let $f = (f_1, \ldots, f_m)\subset \mathbb{Q}[y][x]$ with $y = (y_1, \ldots, y_t)$ and $x…

Symbolic Computation · Computer Science 2021-12-22 Huu Phuoc Le , Mohab Safey El Din

We study a class of bivariate deformed Hermite polynomials and some of their properties using classical analytic techniques and the Wigner map. We also prove the positivity of certain determinants formed by the deformed polynomials. Along…

Mathematical Physics · Physics 2014-10-21 S. Twareque Ali , Mourad E. H. Ismail , Nurisya M. Shah

We consider the problem of finding the isolated common roots of a set of polynomial functions defining a zero-dimensional ideal I in a ring R of polynomials over C. Normal form algorithms provide an algebraic approach to solve this problem.…

Algebraic Geometry · Mathematics 2018-12-10 Bernard Mourrain , Simon Telen , Marc Van Barel

The method of constructing Hermite trigonometric polynomials, which interpolate the values of a certain periodic function and its derivatives up to (including ) the -th ( ) order in nodes of a uniform grid, is considered. The proposed…

Numerical Analysis · Mathematics 2019-02-13 V. P. Denysiuk

Matrix-vector multiplication is one of the most fundamental computing primitives. Given a matrix $A\in\mathbb{F}^{N\times N}$ and a vector $b$, it is known that in the worst case $\Theta(N^2)$ operations over $\mathbb{F}$ are needed to…

Data Structures and Algorithms · Computer Science 2017-11-21 Christopher De Sa , Albert Gu , Rohan Puttagunta , Christopher Ré , Atri Rudra

Given a symmetric nonnegative matrix $A$, symmetric nonnegative matrix factorization (symNMF) is the problem of finding a nonnegative matrix $H$, usually with much fewer columns than $A$, such that $A \approx HH^T$. SymNMF can be used for…

Numerical Analysis · Computer Science 2016-10-07 Arnaud Vandaele , Nicolas Gillis , Qi Lei , Kai Zhong , Inderjit Dhillon

Solving zero-dimensional polynomial systems using Gr\"obner bases is usually done by, first, computing a Gr\"obner basis for the degree reverse lexicographic order, and next computing the lexicographic Gr\"obner basis with a change of order…

Symbolic Computation · Computer Science 2022-05-17 Jérémy Berthomieu , Vincent Neiger , Mohab Safey El Din

Structured canonical forms under unitary and suitable structure-preserving similarity transformations for normal and (skew-)Hamiltonian as well as normal and per(skew)-Hermitian matrices are proposed. Moreover, an algorithm for computing…

Numerical Analysis · Mathematics 2024-03-19 Erna Begovic , Heike Fassbender , Philip Saltenberger

We investigate the algebra and combinatorics of an analogue of the Hermite normal form that classifies finite-index submodules of $\mathbb F_q[[T]]^d$. We identity both normal forms as instances of Gr\"obner basis theory under different…

Combinatorics · Mathematics 2025-08-12 Yifeng Huang , Ruofan Jiang

Toeplitz matrices are abundant in computational mathematics, and there is a rich literature on the development of fast and superfast algorithms for solving linear systems involving such matrices. Any Toeplitz matrix can be transformed into…

Numerical Analysis · Mathematics 2025-06-27 Bernhard Beckermann , Daniel Kressner , Heather Wilber

Nonnegative matrix factorization (NMF) has an established reputation as a useful data analysis technique in numerous applications. However, its usage in practical situations is undergoing challenges in recent years. The fundamental factor…

Machine Learning · Computer Science 2016-05-04 Mariano Tepper , Guillermo Sapiro

Hierarchical matrices approximate a given matrix by a decomposition into low-rank submatrices that can be handled efficiently in factorized form. $\mathcal{H}^2$-matrices refine this representation following the ideas of fast multipole…

Numerical Analysis · Mathematics 2024-04-24 Steffen Börm

Deep learning has been extensively utilized for PolSAR image classification. However, most existing methods transform the polarimetric covariance matrix into a real- or complex-valued vector to comply with standard deep learning frameworks…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Junfei Shi , Yuke Li , Mengmeng Nie , Fang Liu , Haiyan Jin , Junhuai Li , Weisi Lin

We first consider the problem of approximating a few eigenvalues of a rational matrix-valued function closest to a prescribed target. It is assumed that the proper rational part of the rational matrix-valued function is expressed in the…

Numerical Analysis · Mathematics 2022-01-10 Rifqi Aziz , Emre Mengi , Matthias Voigt

The computation of the sparse principal component of a matrix is equivalent to the identification of its principal submatrix with the largest maximum eigenvalue. Finding this optimal submatrix is what renders the problem…

Information Theory · Computer Science 2013-12-23 Megasthenis Asteris , Dimitris S. Papailiopoulos , George N. Karystinos

Pseudo-hermitian matrices are matrices hermitian with respect to an indefinite metric. They can be thought of as the truncation of pseudo-hermitian operators, defined over some Krein space, together with the associated metric, to a finite…

Mathematical Physics · Physics 2022-02-03 Joshua Feinberg , Roman Riser

In many applications it is important to understand the sensitivity of eigenvalues of a matrix polynomial to perturbations of the polynomial. The sensitivity commonly is described by condition numbers or pseudospectra. However, the…

Numerical Analysis · Mathematics 2017-04-06 Silvia Noschese , Lothar Reichel

A blend of two Taylor series for the same smooth real- or complex-valued function of a single variable can be useful for approximation. We use an explicit formula for a two-point Hermite interpolational polynomial to construct such blends.…

Mathematical Software · Computer Science 2020-12-01 Robert M. Corless , Erik Postma

A Las Vegas randomized algorithm is given to compute the Hermite normal form of a nonsingular integer matrix $A$ of dimension $n$. The algorithm uses quadratic integer multiplication and cubic matrix multiplication and has running time…

Data Structures and Algorithms · Computer Science 2023-08-29 Stavros Birmpilis , George Labahn , Arne Storjohann

We consider the approximation of the inverse of the finite element stiffness matrix in the data sparse $\mathcal{H}$-matrix format. For a large class of shape regular but possibly non-uniform meshes including graded meshes, we prove that…

Numerical Analysis · Mathematics 2024-07-25 Niklas Angleitner , Markus Faustmann , Jens Markus Melenk