The join set of a finite collection of smooth embedded submanifolds of a mutual vector space is defined as their Minkowski sum. Join decompositions generalize some ubiquitous decompositions in multilinear algebra, namely tensor rank, Waring, partially symmetric rank and block term decompositions. This paper examines the numerical sensitivity of join decompositions to perturbations; specifically, we consider the condition number for general join decompositions. It is characterized as a distance to a set of ill-posed points in a supplementary product of Grassmannians. We prove that this condition number can be computed efficiently as the smallest singular value of an auxiliary matrix. For some special join sets, we characterized the behavior ...
Copyright © by SIAM. Coupled tensor decompositions are becoming increasingly important in signal pro...
Multidimensional data, or tensors, arise natura lly in data analysis applications. Hitchcock&##39;s ...
We present a new algorithm that can output the rank-decomposition of width at most k of a graph if s...
Join decompositions generalize some ubiquitous decompositions in multilinear algebra, namely tensor ...
ensors are employed in a growing number of applications. Just as the matrix decomposition framework ...
Tensors are employed in a growing number of applications. Just as the matrix decomposition framework...
The concept of rank partition of a family of vectors v1,..., vm is a generalization of that has been...
The tensor rank decomposition problem consists of recovering the unique parameters of the decomposit...
The tensor rank decomposition problem consists of recovering the unique parameters of the decomposit...
Abstract This paper illustrates how methods such as homotopy continuation and monodromy, when combin...
We present a constant-round algorithm in the massively parallel computation(MPC) model for evaluatin...
Hitchcock's rank decompositon---also known as the CANDECOMP/PARAFAC tensor decomposition---may be co...
A geometric join is the union of all colorful simplices spanned by a colored point set in the d-dime...
National audienceIn this work, we present recent results concerning decompositions of tensors and en...
National audienceIn this work, we present recent results concerning decompositions of tensors and en...
Copyright © by SIAM. Coupled tensor decompositions are becoming increasingly important in signal pro...
Multidimensional data, or tensors, arise natura lly in data analysis applications. Hitchcock&##39;s ...
We present a new algorithm that can output the rank-decomposition of width at most k of a graph if s...
Join decompositions generalize some ubiquitous decompositions in multilinear algebra, namely tensor ...
ensors are employed in a growing number of applications. Just as the matrix decomposition framework ...
Tensors are employed in a growing number of applications. Just as the matrix decomposition framework...
The concept of rank partition of a family of vectors v1,..., vm is a generalization of that has been...
The tensor rank decomposition problem consists of recovering the unique parameters of the decomposit...
The tensor rank decomposition problem consists of recovering the unique parameters of the decomposit...
Abstract This paper illustrates how methods such as homotopy continuation and monodromy, when combin...
We present a constant-round algorithm in the massively parallel computation(MPC) model for evaluatin...
Hitchcock's rank decompositon---also known as the CANDECOMP/PARAFAC tensor decomposition---may be co...
A geometric join is the union of all colorful simplices spanned by a colored point set in the d-dime...
National audienceIn this work, we present recent results concerning decompositions of tensors and en...
National audienceIn this work, we present recent results concerning decompositions of tensors and en...
Copyright © by SIAM. Coupled tensor decompositions are becoming increasingly important in signal pro...
Multidimensional data, or tensors, arise natura lly in data analysis applications. Hitchcock&##39;s ...
We present a new algorithm that can output the rank-decomposition of width at most k of a graph if s...