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Related papers: On tensor products of matrix factorizations

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We study solutions of the Yang-Baxter equation on a tensor product of an arbitrary finite-dimensional and an arbitrary infinite-dimensional representations of the rank one symmetry algebra. We consider the cases of the Lie algebra sl_2, the…

Mathematical Physics · Physics 2015-03-02 D. Chicherin , S. Derkachov

In this paper, we present a new algorithm and an experimental implementation for factoring elements in the polynomial n'th Weyl algebra, the polynomial n'th shift algebra, and ZZ^n-graded polynomials in the n'th q-Weyl algebra. The most…

Symbolic Computation · Computer Science 2014-04-02 Mark Giesbrecht , Albert Heinle , Viktor Levandovskyy

We present a method to construct "X" form unitary Yang-Baxter $\breve{R}$ matrices, which act on the tensor product space $V_{i}^{j_{1}}\otimes V_{i+1}^{j_{2}}$. We can obtain a set of entangled states for $(2j_{1}+1)\times…

Mathematical Physics · Physics 2015-03-17 Gangcheng Wang , Kang Xue , Chunfang Sun , Guijiao Du

This paper is concerned with the factorization and equivalence problems of multivariate polynomial matrices. We present some new criteria for the existence of matrix factorizations for a class of multivariate polynomial matrices, and obtain…

Symbolic Computation · Computer Science 2020-10-15 Dong Lu , Dingkang Wang , Fanghui Xiao

Numerous algorithms are used for nonnegative matrix factorization under the assumption that the matrix is nearly separable. In this paper, we show how to make these algorithms efficient for data matrices that have many more rows than…

Machine Learning · Computer Science 2018-01-08 Austin R. Benson , Jason D. Lee , Bartek Rajwa , David F. Gleich

Matrix factorization is a simple and effective solution to the recommendation problem. It has been extensively employed in the industry and has attracted much attention from the academia. However, it is unclear what the low-dimensional…

Machine Learning · Computer Science 2018-08-29 Farhan Khawar , Nevin L. Zhang

Let $F\in \mathbb{K}[X, Y ]$ be a polynomial of total degree $D$ defined over a perfect field $\mathbb{K}$ of characteristic zero or greater than $D$. Assuming $F$ separable with respect to $Y$ , we provide an algorithm that computes the…

Algebraic Geometry · Mathematics 2018-12-05 Adrien Poteaux , Martin Weimann

This paper demonstrates how to explicitly construct a bidiagonal factorization of the banded recurrence matrix that appears in mixed multiple orthogonality on the step-line in terms of the coeffcients of the mixed multiple orthogonal…

Classical Analysis and ODEs · Mathematics 2024-10-22 Amílcar Branquinho , Juan EF Díaz , Ana Foulquié-Moreno , Hélder Lima , Manuel Mañas

We generalize recent matrix-based factorization theorems for Lambert series generating functions generating the coefficients $(f \ast 1)(n)$ for some arithmetic function $f$. Our new factorization theorems provide analogs to these…

Number Theory · Mathematics 2019-09-23 Hamed Mousavi , Maxie D. Schmidt

Ouroboros functions have shown some interesting properties when subjected to conventional operations. The aim of this paper is to continue our investigation and prove some additional properties of these functions. Using algebraic methods,…

General Mathematics · Mathematics 2021-07-06 Nathan Thomas Provost

The Jacobi system on a full-line lattice is considered when it contains additional weight factors. A factorization formula is derived expressing the scattering from such a generalized Jacobi system in terms of the scattering from its…

Mathematical Physics · Physics 2018-05-08 Tuncay Aktosun , Abdon E. Choque-Rivero

In this paper we describe new noncommutative factorizations of functions related to $d$-th tensor powers of Carlitz's $\mathbb F_q[\theta]$-module for $d\geq 1$, called higher sine functions. In recent work by the second author,…

Number Theory · Mathematics 2025-03-18 Nathan Green , Federico Pellarin

Multidimensional factorization method is formulated in arbitrary curvilinear coordinates. Particular cases of polar and spherical coordinates are considered and matrix potentials with separating variables are constructed. A new class of…

High Energy Physics - Theory · Physics 2011-03-07 A. A. Andrianov , M. V. Ioffe , Tsu Zhun-Pin

This paper is concerned with the efficient evaluation of higher-order derivatives of functions $f$ that are composed of matrix operations. I.e., we want to compute the $D$-th derivative tensor $\nabla^D f(X) \in \mathbb R^{N^D}$, where…

Data Structures and Algorithms · Computer Science 2016-09-08 Sebastian F. Walter

We present a method to compute the full non-linear deformations of matrix factorizations for ADE minimal models. This method is based on the calculation of higher products in the cohomology, called Massey products. The algorithm yields a…

High Energy Physics - Theory · Physics 2009-11-11 Johanna Knapp , Harun Omer

We present an approach to decomposition and factor analysis of matrices with ordinal data. The matrix entries are grades to which objects represented by rows satisfy attributes represented by columns, e.g. grades to which an image is red, a…

Machine Learning · Computer Science 2013-03-07 Radim Belohlavek , Vilem Vychodil

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

In this paper we investigate factorizations of polynomials over the ring of dual quaternions into linear factors. While earlier results assume that the norm polynomial is real ("motion polynomials"), we only require the absence of real…

Rings and Algebras · Mathematics 2022-02-21 Johannes Siegele , Martin Pfurner , Hans-Peter Schröcker

Data often comes in the form of an array or matrix. Matrix factorization techniques attempt to recover missing or corrupted entries by assuming that the matrix can be written as the product of two low-rank matrices. In other words, matrix…

Machine Learning · Computer Science 2015-12-16 Gintare Karolina Dziugaite , Daniel M. Roy

Decomposing tensors into orthogonal factors is a well-known task in statistics, machine learning, and signal processing. We study orthogonal outer product decompositions where the factors in the summands in the decomposition are required to…

Machine Learning · Statistics 2013-09-13 Franz J. Király
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