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Waring problem for forms is important and classical in mathematics. It has been widely investigated because of its wide applications in several areas. In this paper, we consider the Waring problem for binary forms with complex coefficients.…

Algebraic Geometry · Mathematics 2019-01-25 Laura Brustenga i Moncusí , Shreedevi K. Masuti

We show that in finite-dimensional nonlinear approximations, the best $r$-term approximant of a function $f$ almost always exists over $\mathbb{C}$ but that the same is not true over $\mathbb{R}$, i.e., the infimum $\inf_{f_1,\dots,f_r \in…

Numerical Analysis · Mathematics 2018-09-07 Yang Qi , Mateusz Michałek , Lek-Heng Lim

Tensor completion recovers a multi-dimensional array from a limited number of measurements. Using the recently proposed tensor ring (TR) decomposition, in this paper we show that a d-order tensor of dimensional size n and TR rank r can be…

Machine Learning · Computer Science 2020-03-17 Huyan Huang , Yipeng Liu , Ce Zhu

We provide a coordinate-free proof that real $2 \times 2 \times 2$ rank three tensors do not have optimal rank two approximations with respect to the Frobenius norm. This result was first proved in by considering the ${\text{GL}(V^1) \times…

Algebraic Geometry · Mathematics 2022-03-16 David Warren Katz

The hierarchical (multi-linear) rank of an order-$d$ tensor is key in determining the cost of representing a tensor as a (tree) Tensor Network (TN). In general, it is known that, for a fixed accuracy, a tensor with random entries cannot be…

Numerical Analysis · Mathematics 2022-01-12 Mazen Ali

We define three types of upper (and lower) triangular blocked tensors, which are all generalizations of the triangular blocked matrices. We study some basic properties and characterizations of these three types of triangular blocked…

Rings and Algebras · Mathematics 2016-04-29 Jiayu Shao , Lihua You

We present a scalable Bayesian model for low-rank factorization of massive tensors with binary observations. The proposed model has the following key properties: (1) in contrast to the models based on the logistic or probit likelihood,…

Machine Learning · Statistics 2015-08-19 Changwei Hu , Piyush Rai , Lawrence Carin

In this paper, we investigate the sample size requirement for a general class of nuclear norm minimization methods for higher order tensor completion. We introduce a class of tensor norms by allowing for different levels of coherence, which…

Statistics Theory · Mathematics 2016-06-14 Ming Yuan , Cun-Hui Zhang

The aim of this paper is twofold. The first part is concerned with the associated and the so-called co-polynomials, i.e. new sequences obtained when finite perturbations of the recurrence coefficients are considered. In the second part we…

Classical Analysis and ODEs · Mathematics 2021-01-05 Abdessadek Saib

We give the stratification by the symmetric tensor rank of all degree $d \ge 9$ homogeneous polynomials with border rank $5$ and which depend essentially on at least 5 variables, extending previous works (A. Bernardi, A. Gimigliano, M.…

Algebraic Geometry · Mathematics 2017-02-08 Edoardo Ballico

The tensor train (TT) rank has received increasing attention in tensor completion due to its ability to capture the global correlation of high-order tensors ($\textrm{order} >3$). For third order visual data, direct TT rank minimization has…

Computer Vision and Pattern Recognition · Computer Science 2020-04-30 Meng Ding , Ting-Zhu Huang , Xi-Le Zhao , Michael K. Ng , Tian-Hui Ma

We study the structure of the Fourier coefficients of low degree multivariate polynomials over finite fields. We consider three properties: (i) the number of nonzero Fourier coefficients; (ii) the sum of the absolute value of the Fourier…

Combinatorics · Mathematics 2016-03-15 Shachar Lovett

The concept of tensor rank, introduced in the twenties, has been popularized at the beginning of the seventies. This has allowed to carry out Factor Analysis on arrays with more than two indices. The generic rank may be seen as an upper…

Other Computer Science · Computer Science 2008-02-19 P. Comon , J. ten Berge

We develop a notion of {\em inner rank} as a tool for obtaining lower bounds on the rank of matrix multiplication tensors. We use it to give a short proof that the border rank (and therefore rank) of the tensor associated with $n\times n$…

Computational Complexity · Computer Science 2019-05-15 Joel Friedman

In solving a system of $n$ linear equations in $d$ variables $Ax=b$, the condition number of the $n,d$ matrix $A$ measures how much errors in the data $b$ affect the solution $x$. Estimates of this type are important in many inverse…

Machine Learning · Computer Science 2020-04-29 Tomaso Poggio , Gil Kur , Andrzej Banburski

It is well-known that tensor decompositions show separations, that is, that constraints on local terms (such as positivity) may entail an arbitrarily high cost in their representation. Here we show that many of these separations disappear…

Optimization and Control · Mathematics 2021-09-03 Gemma De las Cuevas , Andreas Klingler , Tim Netzer

We present an $O^*(|\mathbb{F}|^{\min\left\{R,\ \sum_{d\ge 2} n_d\right\} + (R-n_0)(\sum_{d\ne 0} n_d)})$-time algorithm for determining whether the rank of a concise tensor $T\in\mathbb{F}^{n_0\times\dots\times n_{D-1}}$ is $\le R$,…

Computational Complexity · Computer Science 2025-02-19 Jason Yang

We study bosonic tensor field theories with sextic interactions in $d<3$ dimensions. We consider two models, with rank-3 and rank-5 tensors, and $U(N)^3$ and $O(N)^5$ symmetry, respectively. For both of them we consider two variations: one…

High Energy Physics - Theory · Physics 2021-09-17 Dario Benedetti , Nicolas Delporte , Sabine Harribey , Ritam Sinha

We consider $\ell_1$-Rank-$r$ Approximation over GF(2), where for a binary $m\times n$ matrix ${\bf A}$ and a positive integer $r$, one seeks a binary matrix ${\bf B}$ of rank at most $r$, minimizing the column-sum norm $||{\bf A} -{\bf…

Data Structures and Algorithms · Computer Science 2019-04-15 Fedor V. Fomin , Petr A. Golovach , Fahad Panolan , Kirill Simonov

Multiple network alignment is the problem of identifying similar and related regions in a given set of networks. While there are a large number of effective techniques for pairwise problems with two networks that scale in terms of edges,…

Social and Information Networks · Computer Science 2018-09-24 Huda Nassar , Georgios Kollias , Ananth Grama , David F. Gleich
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