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We consider the problem of factorizing a structured 3-way tensor into its constituent Canonical Polyadic (CP) factors. This decomposition, which can be viewed as a generalization of singular value decomposition (SVD) for tensors, reveals…

Machine Learning · Computer Science 2020-07-01 Sirisha Rambhatla , Xingguo Li , Jarvis Haupt

In this paper, we provide local and global convergence guarantees for recovering CP (Candecomp/Parafac) tensor decomposition. The main step of the proposed algorithm is a simple alternating rank-$1$ update which is the alternating version…

Machine Learning · Computer Science 2015-03-05 Animashree Anandkumar , Rong Ge , Majid Janzamin

We investigate the uniqueness of decomposition of general tensors $T\in {\mathbb C}^{n_1+1}\otimes\cdots\otimes{\mathbb C}^{n_r+1}$ as a sum of tensors of rank $1$. This is done extending the theory developed in a previous paper by the…

Algebraic Geometry · Mathematics 2020-09-03 Alex Casarotti , Massimiliano Mella

We propose a new error bound for the solution of tensor complementarity problem TCP$(q, \mathcal{A})$ given that $\mathcal{A}$ is a $P$-tensor and $q$ is a real vector. We show that the proposed error bound is sharper than the earlier…

Optimization and Control · Mathematics 2022-09-30 R. Deb , A. Dutta , A. K. Das

Hermitian tensors are generalizations of Hermitian matrices, but they have very different properties. Every complex Hermitian tensor is a sum of complex Hermitian rank-1 tensors. However, this is not true for the real case. We study basic…

Numerical Analysis · Mathematics 2020-04-29 Jiawang Nie , Zi Yang

Orthogonal decomposition of tensors is a generalization of the singular value decomposition of matrices. In this paper, we study the spectral theory of orthogonally decomposable tensors. For such a tensor, we give a description of its…

Spectral Theory · Mathematics 2016-04-27 Elina Robeva , Anna Seigal

The cone of positive-semidefinite (PSD) matrices is fundamental in convex optimization, and we extend this notion to tensors, defining PSD tensors, which correspond to separable quantum states. We study the convex optimization problem over…

Optimization and Control · Mathematics 2025-11-10 Liding Xu , Ye-Chao Liu , Sebastian Pokutta

This paper proposes an efficient algorithm for testing copositivity of homogeneous polynomials over the positive semidefinite cone. The algorithm is based on a novel matrix optimization reformulation and requires solving a hierarchy of…

Optimization and Control · Mathematics 2026-01-13 Lei Huang , Lingling Xie

The detection and quantification of quantum coherence play significant roles in quantum information processing. We present an efficient way of tomographic witnessing for both theoretical and experimental detection of coherence. We prove…

Quantum Physics · Physics 2021-05-13 Bang-Hai Wang , Si-Qi Zhou , Zhihao Ma , Shao-Ming Fei

In this work, we consider the optimization formulation for symmetric tensor decomposition recently introduced in the Subspace Power Method (SPM) of Kileel and Pereira. Unlike popular alternative functionals for tensor decomposition, the SPM…

Optimization and Control · Mathematics 2021-11-01 Joe Kileel , Timo Klock , João M. Pereira

Tensor factorization arises in many machine learning applications, such knowledge base modeling and parameter estimation in latent variable models. However, numerical methods for tensor factorization have not reached the level of maturity…

Machine Learning · Computer Science 2015-05-20 Volodymyr Kuleshov , Arun Tejasvi Chaganty , Percy Liang

This paper is concerned with the computation of the principal components for a general tensor, known as the tensor principal component analysis (PCA) problem. We show that the general tensor PCA problem is reducible to its special case…

Optimization and Control · Mathematics 2013-11-19 Bo Jiang , Shiqian Ma , Shuzhong Zhang

We consider the line spectral estimation problem which aims to recover a mixture of complex sinusoids from a small number of randomly observed time domain samples. Compressed sensing methods formulates line spectral estimation as a sparse…

Numerical Analysis · Computer Science 2015-12-11 Jun Fang , Linxiao Yang , Hongbin Li

In this paper, we consider the {\it generalized polynomial complementarity problem} (GPCP), which covers the recently introduced {\it polynomial complementarity problem} (PCP) and the well studied {\it tensor complementarity problem} (TCP)…

Optimization and Control · Mathematics 2019-05-03 Liyun Ling , Chen Ling , Hongjin He

The Canonical Polyadic decomposition (CPD) is a convenient and intuitive tool for tensor factorization; however, for higher-order tensors, it often exhibits high computational cost and permutation of tensor entries, these undesirable…

Numerical Analysis · Computer Science 2018-09-05 Anh-Huy Phan , Andrzej Cichocki , Ivan Oseledets , Salman Ahmadi Asl , Giuseppe Calvi , Danilo Mandic

We study symmetric tensor decompositions, i.e. decompositions of the input symmetric tensor T of order 3 as sum of r 3rd-order tensor powers of u_i where u_i are vectors in \C^n. In order to obtain efficient decomposition algorithms, it is…

Data Structures and Algorithms · Computer Science 2025-03-12 Pascal Koiran , Subhayan Saha

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

Let T be a general complex tensor of format $(n_1,...,n_d)$. When the fraction $\prod_in_i/[1+\sum_i(n_i-1)]$ is an integer, and a natural inequality (called balancedness) is satisfied, it is expected that T has finitely many minimal…

Algebraic Geometry · Mathematics 2025-10-17 Jonathan D. Hauenstein , Luke Oeding , Giorgio Ottaviani , Andrew J. Sommese

Copositive and completely positive matrices play an increasingly important role in Applied Mathematics, namely as a key concept for approximating NP-hard optimization problems. The cone of copositive matrices of a given order and the cone…

Optimization and Control · Mathematics 2017-01-31 Naomi Shaked-Monderer , Abraham Berman , Immanuel M. Bomze , Florian Jarre , Werner Schachinger

In this paper, it is proved that (strict) copositivity of a symmetric tensor $\mathcal{A}$ is equivalent to the fact that every principal sub-tensor of $\mathcal{A}$ has no a (non-positive) negative $H^{++}$-eigenvalue. The necessary and…

Optimization and Control · Mathematics 2022-02-09 Yisheng Song , Liqun Qi
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