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Related papers: Waring, tangential and cactus decompositions

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We present an algorithm to recover a minimal local apolar scheme to a homogeneous polynomial $F$. The socle degree of the scheme determines whether it is evinced by a Generalized Additive Decomposition (GAD) of $F$ or of an extension. We…

Algebraic Geometry · Mathematics 2025-08-22 Alessandra Bernardi , Oriol Reig Fité

Tensors are ubiquitous in science and engineering and tensor factorization approaches have become important tools for the characterization of higher order structure. Factorizations includes the outer-product rank Canonical Polyadic…

Machine Learning · Statistics 2023-10-05 Jesper Løve Hinrich , Morten Mørup

Tucker decomposition is the cornerstone of modern machine learning on tensorial data analysis, which have attracted considerable attention for multiway feature extraction, compressive sensing, and tensor completion. The most challenging…

Machine Learning · Computer Science 2015-05-12 Qibin Zhao , Liqing Zhang , Andrzej Cichocki

We give an algorithm for removing stackiness from smooth, tame Artin stacks with abelian stabilisers by repeatedly applying stacky blow-ups. The construction works over a general base and is functorial with respect to base change and…

Algebraic Geometry · Mathematics 2019-02-20 Daniel Bergh

Higher-order low-rank tensors naturally arise in many applications including hyperspectral data recovery, video inpainting, seismic data recon- struction, and so on. We propose a new model to recover a low-rank tensor by simultaneously…

Numerical Analysis · Computer Science 2015-07-07 Yangyang Xu , Ruru Hao , Wotao Yin , Zhixun Su

We establish basic information about border rank algorithms for the matrix multiplication tensor and other tensors with symmetry. We prove that border rank algorithms for tensors with symmetry (such as matrix multiplication and the…

Algebraic Geometry · Mathematics 2016-02-01 J. M. Landsberg , Mateusz Michałek

Despite their high accuracy, complex neural networks demand significant computational resources, posing challenges for deployment on resource constrained devices such as mobile phones and embedded systems. Compression algorithms have been…

Machine Learning · Computer Science 2025-09-23 Ali Aghababaei-Harandi , Massih-Reza Amini

Canonical Polyadic Decomposition (CPD) of a third-order tensor is a minimal decomposition into a sum of rank-$1$ tensors. We find new mild deterministic conditions for the uniqueness of individual rank-$1$ tensors in CPD and present an…

Spectral Theory · Mathematics 2016-07-20 Ignat Domanov , Lieven De Lathauwer

Deterministic recursive algorithms for the computation of matrix triangular decompositions with permutations like LU and Bruhat decomposition are presented for the case of commutative domains. This decomposition can be considered as a…

Symbolic Computation · Computer Science 2017-02-24 Gennadi Malaschonok , Anton Scherbinin

Canonical Polyadic (also known as Candecomp/Parafac) Decomposition (CPD) of a higher-order tensor is decomposition in a minimal number of rank-1 tensors. In Part I, we gave an overview of existing results concerning uniqueness and presented…

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

While every matrix admits a singular value decomposition, in which the terms are pairwise orthogonal in a strong sense, higher-order tensors typically do not admit such an orthogonal decomposition. Those that do have attracted attention…

Algebraic Geometry · Mathematics 2015-12-29 Ada Boralevi , Jan Draisma , Emil Horobet , Elina Robeva

We introduce the concise secant varieties, which are, informally speaking, modular partial desingularisations of secant varieties to Segre embeddings. More precisely, they are projective and birational to the abstract secant varieties, yet…

Algebraic Geometry · Mathematics 2026-04-29 Jakub Jagiełła , Joachim Jelisiejew

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

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

In this paper, we propose a general algorithmic framework to solve a class of optimization problems on the product of complex Stiefel manifolds based on the matrix polar decomposition. We establish the weak convergence, global convergence…

Numerical Analysis · Mathematics 2020-06-16 Jianze Li , Shuzhong Zhang

We consider the problem of finding the smallest or largest entry of a tensor of order N that is specified via its rank decomposition. Stated in a different way, we are given N sets of R-dimensional vectors and we wish to select one vector…

Signal Processing · Electrical Eng. & Systems 2023-12-25 Nicholas D. Sidiropoulos , Paris Karakasis , Aritra Konar

Irreducible Cartesian tensors (ICTs) play a crucial role in the design of equivariant graph neural networks, as well as in theoretical chemistry and chemical physics. Meanwhile, the design space of available linear operations on tensors…

Machine Learning · Computer Science 2025-08-29 Shihao Shao , Yikang Li , Zhouchen Lin , Qinghua Cui

We provide simple criteria and algorithms for expressing homogeneous polynomials as sums of powers of independent linear forms, or equivalently, for decomposing symmetric tensors into sums of rank-1 symmetric tensors of linearly independent…

Rings and Algebras · Mathematics 2021-10-08 Hua-Lin Huang , Huajun Lu , Yu Ye , Chi Zhang

We give a spectral algorithm for decomposing overcomplete order-4 tensors, so long as their components satisfy an algebraic non-degeneracy condition that holds for nearly all (all but an algebraic set of measure $0$) tensors over…

Machine Learning · Computer Science 2022-03-08 Samuel B. Hopkins , Tselil Schramm , Jonathan Shi

Phylogenetic networks are a generalization of evolutionary or phylogenetic trees that are commonly used to represent the evolution of species which cross with one another. A special type of phylogenetic network is an {\em $X$-cactus}, which…

Populations and Evolution · Quantitative Biology 2021-09-08 Andrew Francis , Katharina T. Huber , Vincent Moulton , Taoyang Wu