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In this paper we propose an iterative algorithm to find out the spectral radius of nonnegative tensors. This algorithm is an extension of the smoothing method for finding the largest eigenvalue of a nonnegative matrix \cite{s14}. For…

Spectral Theory · Mathematics 2011-02-15 Yuning Yang , Qingzhi Yang , Yanguang Li

Recent work on eigenvalues and eigenvectors for tensors of order m >= 3 has been motivated by applications in blind source separation, magnetic resonance imaging, molecular conformation, and more. In this paper, we consider methods for…

Numerical Analysis · Mathematics 2011-11-14 Tamara G. Kolda , Jackson R. Mayo

Efficient solvers for tensor eigenvalue problems are important tools for the analysis of higher-order data sets. Here we introduce, analyze and demonstrate an extrapolation method to accelerate the widely used shifted symmetric higher order…

Numerical Analysis · Mathematics 2023-07-25 Sara Pollock , Rhea Shroff

An M-eigenvalue of a nonnegative biquadratic tensor is referred to as an M$^+$-eigenvalue if it has a pair of nonnegative M-eigenvectors. If furthermore that pair of M-eigenvectors is positive, then that M$^+$-eigenvalue is called an…

Numerical Analysis · Mathematics 2025-03-28 Chunfeng Cui , Liqun Qi

In this paper, we propose the tensor Noda iteration (NI) and its inexact version for solving the eigenvalue problem of a particular class of tensor pairs called generalized $\mathcal{M}$-tensor pairs. A generalized $\mathcal{M}$-tensor pair…

Numerical Analysis · Mathematics 2023-03-03 Wanli Ma , Weiyang Ding , Yimin Wei

A numerical irreducible decomposition for a polynomial system provides representations for the irreducible factors of all positive dimensional solution sets of the system, separated from its isolated solutions. Homotopy continuation methods…

Mathematical Software · Computer Science 2018-06-19 Jan Verschelde

Unlike matrix completion, tensor completion does not have an algorithm that is known to achieve the information-theoretic sample complexity rate. This paper develops a new algorithm for the special case of completion for nonnegative…

Machine Learning · Computer Science 2022-05-25 Caleb Bugg , Chen Chen , Anil Aswani

This work considers the problem of estimating the parameters of negative mixture models, i.e. mixture models that possibly involve negative weights. The contributions of this paper are as follows. (i) We show that every rational probability…

Machine Learning · Computer Science 2014-09-22 Guillaume Rabusseau , François Denis

Quadratic eigenvalue problems (QEP) and more generally polynomial eigenvalue problems (PEP) are among the most common types of nonlinear eigenvalue problems. Both problems, especially the QEP, have extensive applications. A typical approach…

Numerical Analysis · Mathematics 2017-11-07 Yiling You , Jose Israel Rodriguez , Lek-Heng Lim

We construct an effective algorithmic method to compute the homological monodromy of a complex polynomial which is tame. As an application we show the existence of conjugated polynomials in a number field which are not topologically…

Algebraic Geometry · Mathematics 2007-05-23 M. Escario

The main purpose of this paper is to study non-commutative ternary Nambu-Poisson algebras and their Hom-type version. We provide construction results dealing with tensor product and direct sums of two (non-commutative) ternary…

Rings and Algebras · Mathematics 2014-10-09 Hanene Amri , Abdenacer Makhlouf

The manuscript addresses the problem of finding all solutions of power flow equations or other similar nonlinear system of algebraic equations. This problem arises naturally in a number of power systems contexts, most importantly in the…

Chaotic Dynamics · Physics 2014-08-13 Dhagash Mehta , Hung Nguyen , Konstantin Turitsyn

We introduce the concept of homotopy iterators for performing polynomial homotopy continuation tasks in a memory efficient manner. The main idea is to push forward an iterator for the start solutions of a homotopy via the function which…

Algebraic Geometry · Mathematics 2025-09-11 Paul Breiding , Taylor Brysiewicz , Hannah Friedman

The eigenpair here means the twins consist of eigenvalue and its eigenvector. This paper introduces the three steps of our study on computing the maximal eigenpair. In the first two steps, we construct efficient initials for a known but…

General Mathematics · Mathematics 2017-11-29 Mu-Fa Chen

Latent variable models with hidden binary units appear in various applications. Learning such models, in particular in the presence of noise, is a challenging computational problem. In this paper we propose a novel spectral approach to this…

Machine Learning · Statistics 2018-02-28 Ariel Jaffe , Roi Weiss , Shai Carmi , Yuval Kluger , Boaz Nadler

We introduce $\hat{H}$-eigenvalue for $2m$-th order $n$-dimensional complex tensors. Then we determine several checkable inclusion sets for $\hat{H}$-eigenvalues and derive some criterions for the Hermitian positive definiteness…

Spectral Theory · Mathematics 2025-08-19 Haojie Chen , Yang Yang

Eigenvector continuation is a computational method that finds the extremal eigenvalues and eigenvectors of a Hamiltonian matrix with one or more control parameters. It does this by projection onto a subspace of eigenvectors corresponding to…

Nuclear Theory · Physics 2021-01-22 Avik Sarkar , Dean Lee

This article develops a new predictor-corrector algorithm for numerical path tracking in the context of polynomial homotopy continuation. In the corrector step it uses a newly developed Newton corrector algorithm which rejects an initial…

Numerical Analysis · Mathematics 2020-03-24 Sascha Timme

In this paper we present a new approach to computing homology (with field coefficients) and persistent homology. We use concepts from discrete Morse theory, to provide an algorithm which can be expressed solely in terms of simple graph…

Algebraic Topology · Mathematics 2012-10-26 Paweł Dłotko , Hubert Wagner

Developing efficient and guaranteed nonconvex algorithms has been an important challenge in modern machine learning. Algorithms with good empirical performance such as stochastic gradient descent often lack theoretical guarantees. In this…

Machine Learning · Statistics 2017-06-15 Anima Anandkumar , Yuan Deng , Rong Ge , Hossein Mobahi