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Related papers: On unique tensor rank decomposition of 3-tensors

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We give a sufficient criterion for a lower bound of the cactus rank of a tensor. Then we refine that criterion in order to be able to give an explicit sufficient condition for a non-redundant decomposition of a tensor to be minimal and…

Algebraic Geometry · Mathematics 2017-05-08 Edoardo Ballico , Alessandra Bernardi , Luca Chiantini , Elena Guardo

We prove a generalization to Jennrich's uniqueness theorem for tensor decompositions in the undercomplete setting. Our uniqueness theorem is based on an alternative definition of the standard tensor decomposition, which we call…

Computational Complexity · Computer Science 2025-10-31 Pascal Koiran , Rafael Oliveira

A theorem of J. Kruskal from 1977, motivated by a latent-class statistical model, established that under certain explicit conditions the expression of a 3-dimensional tensor as the sum of rank-1 tensors is essentially unique. We give a new…

Rings and Algebras · Mathematics 2009-01-15 John A. Rhodes

We present several conditions for generic uniqueness of tensor decompositions of multilinear rank (1,L_{1}, L_{1}),..., (1, L_{R}, L_{R}) terms. In geometric language, we prove that the joins of relevant subspace varieties are not…

Algebraic Geometry · Mathematics 2013-01-08 Ming Yang

The tensor rank decomposition problem consists of recovering the unique set of parameters representing a robustly identifiable low-rank tensor when the coordinate representation of the tensor is presented as input. A condition number for…

Algebraic Geometry · Mathematics 2022-09-02 Nick Vannieuwenhoven

Canonical Polyadic Decomposition (CPD) of a higher-order tensor is decomposition in a minimal number of rank-1 tensors. We give an overview of existing results concerning uniqueness. We present new, relaxed, conditions that guarantee…

Spectral Theory · Mathematics 2013-07-05 Ignat Domanov , Lieven De Lathauwer

In this paper, we introduce a new tensor decomposition for third order tensors, which decomposes a third order tensor to three third order low rank tensors in a balanced way. We call such a decomposition the triple decomposition, and the…

Numerical Analysis · Mathematics 2020-03-03 Liqun Qi , Yannan Chen , Mayank Bakshi , Xinzhen Zhang

The paper deals with the computation of the rank and the identifiability of a specific ternary form. Often, one knows some short Waring decomposition of a given form, and the problem is to determine whether the decomposition is minimal and…

Algebraic Geometry · Mathematics 2022-03-08 Elena Angelini , Luca Chiantini

We prove (without exceptions) the existence of irredundant tensor decompositions with the number of addenda equal to rank $+1$. We also discuss the existence of decompositions with more than the tensor rank terms, which are concise, while…

Algebraic Geometry · Mathematics 2020-02-17 Edoardo Ballico

Canonical Polyadic Decomposition (CPD) represents a third-order tensor as the minimal sum of rank-1 terms. Because of its uniqueness properties the CPD has found many concrete applications in telecommunication, array processing, machine…

Spectral Theory · Mathematics 2019-12-06 Ignat Domanov , Lieven De Lathauwer

We consider the problem of low canonical polyadic (CP) rank tensor completion. A completion is a tensor whose entries agree with the observed entries and its rank matches the given CP rank. We analyze the manifold structure corresponding to…

Machine Learning · Computer Science 2017-04-03 Morteza Ashraphijuo , Xiaodong Wang

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

We present a simple proof that finding a rank-$R$ canonical polyadic decomposition of a 3-dimensional tensor over a finite field $\mathbb{F}$ is fixed-parameter tractable with respect to $R$ and $\mathbb{F}$. We also show a nontrivial upper…

Computational Complexity · Computer Science 2024-06-18 Jason Yang

Kruskal's theorem states that a sum of product tensors constitutes a unique tensor rank decomposition if the so-called k-ranks of the product tensors are large. In this work, we propose a conjecture in which the k-rank condition of…

Combinatorics · Mathematics 2020-08-21 Benjamin Lovitz

One of the main issues in computing a tensor decomposition is how to choose the number of rank-one components, since there is no finite algorithms for determining the rank of a tensor. A commonly used approach for this purpose is to find a…

Computer Vision and Pattern Recognition · Computer Science 2023-09-15 Claudio Turchetti

We propose a new sufficient condition for verifying whether generic rank-r complex tensors of arbitrary order admit a unique decomposition as a linear combination of rank-1 tensors. A practical algorithm is proposed for verifying this…

Algebraic Geometry · Mathematics 2022-09-02 Luca Chiantini , Giorgio Ottaviani , Nick Vannieuwenhoven

In this paper, we analyze the fundamental conditions for low-rank tensor completion given the separation or tensor-train (TT) rank, i.e., ranks of unfoldings. We exploit the algebraic structure of the TT decomposition to obtain the…

Machine Learning · Computer Science 2017-03-23 Morteza Ashraphijuo , Xiaodong Wang

In this paper, we present a method to certify the approximation quality of a low rank tensor to a given third order symmetric tensor. Under mild assumptions, best low rank approximation is attained if a control parameter is zero or…

Optimization and Control · Mathematics 2023-07-21 Shenglong Hu , Defeng Sun , Kim-Chuan Toh

We give a new, constructive uniqueness theorem for tensor decomposition. It applies to order 3 tensors of format $n \times n \times p$ and can prove uniqueness of decomposition for generic tensors up to rank $r=4n/3$ as soon as $p \geq 4$.…

Data Structures and Algorithms · Computer Science 2025-02-12 Pascal Koiran

In this paper, we show that the low rank matrix completion problem can be reduced to the problem of finding the rank of a certain tensor.

Optimization and Control · Mathematics 2013-07-24 Harm Derksen
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