Invariance transformations of polyadic decompositions of matrix multiplication tensors define an equivalence relation on the set of such decompositions. In this paper, we present an algorithm to efficiently decide whether two polyadic decompositions of a given matrix multiplication tensor are equivalent. With this algorithm, we analyze the equivalence classes of decompositions of several matrix multiplication tensors. This analysis is relevant for the study of fast matrix multiplication as it relates to the question of how many essentially different fast matrix multiplication algorithms there exist. This question has been first studied by de Groote, who showed that for the multiplication of 2×2 matrices with 7 active multiplications, all al...
The computation of themodel parameters of a Canonical Polyadic Decom-position (CPD), also known as t...
The Singular Value Decomposition (SVD) of matrices is widely used in least-squares regression, image...
CP) decomposition (CPD) is widely applied to N th-order (N ≥ 3) tensor analysis. Existing CPD method...
Invariance transformations of polyadic decompositions of matrix multiplication tensors define an equ...
ílem této práce je seznámit čtenáře s kanonickým rozkladem tenzorů třetího řádu, konkrétně tenzorů n...
In this thesis, we tackle the problem of matrix multiplication complexity. Matrix multiplication, wh...
Canonical polyadic decomposition (CPD) of a third-order tensor is decomposition in a minimal number ...
more details in : hal-00490248The Canonical Polyadic (CP) decomposition of a tensor is difficult to ...
Canonical polyadic decomposition (CPD) of a higher-order tensor is decomposition into a minimal numb...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
In many applications signals or data vary with respect to several parameters (such as spatial coord...
International audienceIn this paper we propose a novel algorithm to compute the joint eigenvalue dec...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
International audienceThe Canonical Polyadic (CP) tensor decomposition has become an attractive math...
The computation of themodel parameters of a Canonical Polyadic Decom-position (CPD), also known as t...
The Singular Value Decomposition (SVD) of matrices is widely used in least-squares regression, image...
CP) decomposition (CPD) is widely applied to N th-order (N ≥ 3) tensor analysis. Existing CPD method...
Invariance transformations of polyadic decompositions of matrix multiplication tensors define an equ...
ílem této práce je seznámit čtenáře s kanonickým rozkladem tenzorů třetího řádu, konkrétně tenzorů n...
In this thesis, we tackle the problem of matrix multiplication complexity. Matrix multiplication, wh...
Canonical polyadic decomposition (CPD) of a third-order tensor is decomposition in a minimal number ...
more details in : hal-00490248The Canonical Polyadic (CP) decomposition of a tensor is difficult to ...
Canonical polyadic decomposition (CPD) of a higher-order tensor is decomposition into a minimal numb...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
In many applications signals or data vary with respect to several parameters (such as spatial coord...
International audienceIn this paper we propose a novel algorithm to compute the joint eigenvalue dec...
This is the first in a series of papers on rank decompositions of the matrix multiplication tensor. ...
International audienceThe Canonical Polyadic (CP) tensor decomposition has become an attractive math...
The computation of themodel parameters of a Canonical Polyadic Decom-position (CPD), also known as t...
The Singular Value Decomposition (SVD) of matrices is widely used in least-squares regression, image...
CP) decomposition (CPD) is widely applied to N th-order (N ≥ 3) tensor analysis. Existing CPD method...