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In this paper, we consider the tensor completion problem representing the solution in the tensor train (TT) format. It is assumed that tensor is high-dimensional, and tensor values are generated by an unknown smooth function. The assumption…

Numerical Analysis · Mathematics 2020-08-27 Yermek Kapushev , Ivan Oseledets , Evgeny Burnaev

In this paper, we give a further study on $B$-tensors and introduce doubly $B$-tensors that contain $B$-tensors. We show that they have similar properties, including their decompositions and strong relationship with strictly (doubly)…

Spectral Theory · Mathematics 2016-04-29 Lu Ye , Zhongming Chen

In the present paper, some aspects of the finite-dimensional theory of set-inclusive generalized equations are studied. Set-inclusive generalized equations are problems arising in several contexts of optimization and variational analysis,…

Optimization and Control · Mathematics 2018-11-26 Amos Uderzo

This paper studies symmetric tensor decompositions. For symmetric tensors, there exist linear relations of recursive patterns among their entries. Such a relation can be represented by a polynomial, which is called a generating polynomial.…

Numerical Analysis · Mathematics 2015-10-06 Jiawang Nie

We consider the problem of solving mixed random linear equations with $k$ components. This is the noiseless setting of mixed linear regression. The goal is to estimate multiple linear models from mixed samples in the case where the labels…

Machine Learning · Computer Science 2016-08-23 Xinyang Yi , Constantine Caramanis , Sujay Sanghavi

Tensor completion and robust principal component analysis have been widely used in machine learning while the key problem relies on the minimization of a tensor rank that is very challenging. A common way to tackle this difficulty is to…

Machine Learning · Computer Science 2021-05-26 Tao Li , Jinwen Ma

We propose a theory of eigenvalues, eigenvectors, singular values, and singular vectors for tensors based on a constrained variational approach much like the Rayleigh quotient for symmetric matrix eigenvalues. These notions are particularly…

Spectral Theory · Mathematics 2007-05-23 Lek-Heng Lim

Specific definitions of the core and core-EP inverses of complex tensors are introduced. Some characterizations, representations and properties of the core and core-EP inverses are investigated. The results are verified using specific…

One of the key problems in tensor completion is the number of uniformly random sample entries required for recovery guarantee. The main aim of this paper is to study $n_1 \times n_2 \times n_3$ third-order tensor completion based on…

Machine Learning · Statistics 2022-01-25 Guang-Jing Song , Michael K. Ng , Xiongjun Zhang

We present necessary conditions for monotonicity, in one form or another, of fixed point iterations of mappings that violate the usual nonexpansive property. We show that most reasonable notions of linear-type monotonicity of fixed point…

Optimization and Control · Mathematics 2020-03-26 D. Russell Luke , Marc Teboulle , Nguyen H. Thao

Many problems can be formulated as recovering a low-rank tensor. Although an increasingly common task, tensor recovery remains a challenging problem because of the delicacy associated with the decomposition of higher order tensors. To…

Machine Learning · Statistics 2014-05-09 Ming Yuan , Cun-Hui Zhang

We define and study a certain relative tensor product of subfactors over a modular tensor category. This gives a relative tensor product of two completely rational heterotic full local conformal nets with trivial superselection structures…

Operator Algebras · Mathematics 2017-12-01 Yasuyuki Kawahigashi

We consider the linear complementarity problem with uncertain data modeled by intervals, representing the range of possible values. Many properties of the linear complementarity problem (such as solvability, uniqueness, convexity, finite…

Optimization and Control · Mathematics 2025-10-07 Milan Hladík

In this article we establish error bound for linear complementarity problem with $P$-matrix using plus function. We introduce a fundamental quantity associated with a $P$-matrix and show how this quantity is useful in deriving error bounds…

Optimization and Control · Mathematics 2022-09-02 Bharat Kumar , Deepmala , A. Dutta , A. K. Das

Finding the rank of a tensor is a problem that has many applications. Unfortunately it is often very difficult to determine the rank of a given tensor. Inspired by the heuristics of convex relaxation, we consider the nuclear norm instead of…

Optimization and Control · Mathematics 2014-04-23 Harm Derksen

We show that a tensor field of any rank integrates to zero over all broken rays if and only if it is a symmetrized covariant derivative of a lower order tensor which satisfies a symmetry condition at the reflecting part of the boundary and…

Differential Geometry · Mathematics 2020-01-24 Joonas Ilmavirta , Gabriel P. Paternain

A new \emph{S}-type eigenvalue localization set for tensors is derived by breaking $N=\{1,2,\cdots,n\}$ into disjoint subsets $S$ and its complement. It is proved that this new set is tighter than those presented by Qi (Journal of Symbolic…

Combinatorics · Mathematics 2016-02-25 Zhengge Huang , Ligong Wang , Zhong Xu , Jingjing Cui

In this paper we introduce the concept of completeness of sets. We study this property on the set of integers. We examine how this property is preserved as we carry out various operations compatible with sets. We also introduce the problem…

General Mathematics · Mathematics 2021-08-24 Theophilus Agama

Tree tensor networks such as the tensor train format are a common tool for high dimensional problems. The associated multivariate rank and accordant tuples of singular values are based on different matricizations of the same tensor. While…

Numerical Analysis · Mathematics 2019-04-10 Sebastian Krämer

By a tensor we mean an element of a tensor product of vector spaces over a field. Up to a choice of bases in factors of tensor products, every tensor may be coordinatized, that is, represented as an array consisting of numbers. This note is…

Functional Analysis · Mathematics 2019-01-11 R. N. Gumerov , A. S. Sharafutdinov