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In this paper, we introduce almost (strictly) semi-positive tensors, which extend the concept of almost (strictly) semimonotone matrices. Furthermore, we provide insights into the characteristics of the entries within these almost…

Optimization and Control · Mathematics 2024-05-14 Bharat Pratap Chauhan , Dipti Dubey

In this paper, first we introduce the notion of an embedding tensor on a 3-Lie algebra, which naturally induces a 3-Leibniz algebra. Using the derived bracket, we construct a Lie 3-algebra, whose Maurer-Cartan elements are embedding…

Rings and Algebras · Mathematics 2024-03-25 Meiyan Hu , Shuai Hou , Lina Song , Yanqiu Zhou

This paper discusses the computation of real Z-eigenvalues and H-eigenvalues of nonsymmetric tensors. A general nonsymmetric tensor has finitely many Z-eigenvalues, while there may be infinitely many ones for special tensors. In the…

Numerical Analysis · Mathematics 2015-03-25 Jiawang Nie , Xinzhen Zhang

Decompositions of tensors into factor matrices, which interact through a core tensor, have found numerous applications in signal processing and machine learning. A more general tensor model which represents data as an ordered network of…

Numerical Analysis · Computer Science 2016-09-30 Anh-Huy Phan , Andrzej Cichocki , Andre Uschmajew , Petr Tichavsky , George Luta , Danilo Mandic

Finding the rank of a tensor is a problem that has many applications. Unfortunately it is often very difficult to determine the rank of a given tensor. Inspired by the heuristics of convex relaxation, we consider the nuclear norm instead of…

Optimization and Control · Mathematics 2014-04-23 Harm Derksen

Tensors, or multi-linear forms, are important objects in a variety of areas from analytics, to combinatorics, to computational complexity theory. Notions of tensor rank aim to quantify the "complexity" of these forms, and are thus also…

Computational Complexity · Computer Science 2023-06-16 Mandar Juvekar , Arian Nadjimzadah

We establish several mathematical and computational properties of the nuclear norm for higher-order tensors. We show that like tensor rank, tensor nuclear norm is dependent on the choice of base field --- the value of the nuclear norm of a…

Computational Complexity · Computer Science 2016-05-19 Shmuel Friedland , Lek-Heng Lim

Recently, triple decomposition has attracted increasing attention for decomposing third-order tensors into three factor tensors. However, this approach is limited to third-order tensors and enforces uniformity in the lower dimensions across…

Numerical Analysis · Mathematics 2025-11-14 Kunjing Yang , Libin Zheng , Minru Bai

We lay the geometric foundations for the study of the characteristic polynomial of tensors. For symmetric tensors of order $d \geq 3$ and dimension $2$ and symmetric tensors of order $3$ and dimension $3$, we prove that only finitely many…

Algebraic Geometry · Mathematics 2023-08-23 Francesco Galuppi , Fulvio Gesmundo , Ettore Teixeira Turatti , Lorenzo Venturello

Tensor decompositions have rich applications in statistics and machine learning, and developing efficient, accurate algorithms for the problem has received much attention recently. Here, we present a new method built on Kruskal's uniqueness…

Machine Learning · Computer Science 2017-04-20 Miaoyan Wang , Yun S. Song

We introduce an inductive method for the study of the uniqueness of decompositions of tensors, by means of tensors of rank 1. The method is based on the geometric notion of weak defectivity. For three-dimensional tensors of type (a, b, c),…

Algebraic Geometry · Mathematics 2011-03-15 Luca Chiantini , Giorgio Ottaviani

The 5-point tensors have the property that after insertion of the metric tensor $g^{\mu \nu}$ in terms of external momenta, all $g^{\mu \nu}$-contributions in the tensor decomposition cancel. If furthermore the tensors are contracted with…

High Energy Physics - Phenomenology · Physics 2011-11-18 J. Fleischer , T. Riemann

Most regularized tensor regression research focuses on tensors predictors with scalars responses or vectors predictors to tensors responses. We consider the sparse low rank tensor on tensor regression where predictors $\mathcal{X}$ and…

Machine Learning · Computer Science 2022-12-16 Haiyi Mao , Jason Xiaotian Dou

Third order tensors have wide applications in mechanics, physics and engineering. The most famous and useful third order tensor is the piezoelectric tensor, which plays a key role in the piezoelectric effect, first discovered by Curie…

Mathematical Physics · Physics 2017-10-16 Liqun Qi

This paper lies in the intersection of several fields: number theory, lattice theory, multilinear algebra, and scientific computing. We adapt existing solution algorithms for tensor eigenvalue problems to the tensor-train framework. As an…

Numerical Analysis · Mathematics 2017-10-05 Harri Hakula , Pauliina Ilmonen , Vesa Kaarnioja

A symmetric tensor is completely positive (CP) if it is a sum of tensor powers of nonnegative vectors. This paper characterizes completely positive binary tensors. We show that a binary tensor is completely positive if and only if it…

Optimization and Control · Mathematics 2018-08-08 Jinyan Fan , Jiawang Nie , Anwa Zhou

The current paper presents a new approach to multilinear dynamical systems analysis and control. The approach is based upon recent developments in tensor decompositions and a newly defined algebra of circulants. In particular, it is shown…

Machine Learning · Computer Science 2021-09-01 Randy C. Hoover , Kyle Caudle , Karen Braman

Cartesian harmonic tensors are completely symmetric traceless tensors in three dimensional space constructed from the direct product of unit vectors. They are useful in generating expressions for the angular coupling of spherical harmonics…

Classical Physics · Physics 2023-03-14 William C. Parke

This paper introduces the notion of tubular eigenvalues of third-order tensors with respect to T-products of tensors and analyzes their properties. A focus of the paper is to discuss relations between tubular eigenvalues and two alternative…

Numerical Analysis · Mathematics 2023-05-11 Fatemeh P. A. Beik , Yousef Saad

A numerical algorithm to decompose an exact low-rank skew-symmetric tensor into a sum of elementary (rank-$1$) skew-symmetric tensors is introduced. The algorithm uncovers this Grassmann decomposition based on linear relations that are…

Numerical Analysis · Mathematics 2026-01-27 Nick Vannieuwenhoven
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