Add to ORKGInternational audienceWe consider two models: simultaneous CP decomposition of several symmetric tensors of different orders and decoupled representations of multivariate polynomial maps. We show that the two problems are related and propose a unified framework to study the rank properties of these models
We give a robust version of the celebrated result of Kruskal on the uniqueness of tensor decompo-sit...
International audienceSymmetric Tensor Decomposition is a major problem that arises in areas such as...
special session "Tensor Computations in Linear and Multilinear Algebra"Tensor decompositions permit ...
International audienceWe present an algorithm for decomposing a symmetric tensor, of dimension n and...
AbstractWe present an algorithm for decomposing a symmetric tensor, of dimension n and order d, as a...
© 2019 Elsevier B.V. Decoupling multivariate polynomials is useful for obtaining an insight into the...
International audienceA symmetric tensor is a higher order generalization of a symmetric matrix. In ...
International audienceWe introduce various notions of rank for a symmetric tensor, namely: rank, bor...
International audienceIn Engineering, the identification of a linear statistical model is omnipresen...
International audienceIn this paper, we study a polynomial decomposition model that arises in proble...
Accepted to JSCSymmetric tensor decomposition is an important problem with applications in several a...
\u3cp\u3eMultivariate polynomials are often used to model nonlinear behavior, e.g., in parallel Wien...
International audienceIn the paper, we address the important problem of tensor decomposition which c...
Abstract. We present a method to decompose a set of multivariate real polynomials into linear combin...
International audienceWe study the decomposition of a multi-symmetric tensor $T$ as a sum of powers ...
We give a robust version of the celebrated result of Kruskal on the uniqueness of tensor decompo-sit...
International audienceSymmetric Tensor Decomposition is a major problem that arises in areas such as...
special session "Tensor Computations in Linear and Multilinear Algebra"Tensor decompositions permit ...
International audienceWe present an algorithm for decomposing a symmetric tensor, of dimension n and...
AbstractWe present an algorithm for decomposing a symmetric tensor, of dimension n and order d, as a...
© 2019 Elsevier B.V. Decoupling multivariate polynomials is useful for obtaining an insight into the...
International audienceA symmetric tensor is a higher order generalization of a symmetric matrix. In ...
International audienceWe introduce various notions of rank for a symmetric tensor, namely: rank, bor...
International audienceIn Engineering, the identification of a linear statistical model is omnipresen...
International audienceIn this paper, we study a polynomial decomposition model that arises in proble...
Accepted to JSCSymmetric tensor decomposition is an important problem with applications in several a...
\u3cp\u3eMultivariate polynomials are often used to model nonlinear behavior, e.g., in parallel Wien...
International audienceIn the paper, we address the important problem of tensor decomposition which c...
Abstract. We present a method to decompose a set of multivariate real polynomials into linear combin...
International audienceWe study the decomposition of a multi-symmetric tensor $T$ as a sum of powers ...
We give a robust version of the celebrated result of Kruskal on the uniqueness of tensor decompo-sit...
International audienceSymmetric Tensor Decomposition is a major problem that arises in areas such as...
special session "Tensor Computations in Linear and Multilinear Algebra"Tensor decompositions permit ...