invited KeynoteInternational audienceSince the nineties, tensors are increasingly used in Signal Processing and Data Analysis. There exist striking differences between tensors and matrices, some being advantages, and others raising difficulties. These differences are pointed out in this paper while briefly surveying the state of the art. The conclusion is that tensors are omnipresent in real life, implicitly or explicitly, and must be used even if we still know quite little about their properties
International audienceIt has been shown that a best rank-R approximation of an order-k tensor may no...
International audienceThe concept of tensor rank, introduced in the twenties, has been popularized a...
© 1991-2012 IEEE. The widespread use of multisensor technology and the emergence of big data sets ha...
International audienceTensor decompositions are at the core of many Blind Source Separation (BSS) al...
International audienceTensors appear more and more often in signal processing problems, and especial...
Tensors, or multi-linear forms, are important objects in a variety of areas from analytics, to combi...
© 1991-2012 IEEE. Tensors or multiway arrays are functions of three or more indices (i,j,k,⋯)-simila...
The value of data cannot be underestimated in our current digital age. Data mining techniques have a...
International audienceThe concept of tensor rank was introduced in the twenties. In the seventies, w...
Multidimensional data, or tensors, arise natura lly in data analysis applications. Hitchcock&##39;s ...
We analyze data to build a quantitative understanding of the world. Linear algebra is the foundation...
The widespread use of multi-sensor technology and the emergence of big datasets has highlighted the ...
In many applications signals or data vary with respect to several parameters (such as spatial coord...
International audienceIs has been shown that a best rank-R approximation of an order-k tensor may no...
Tensor decomposition methods and multilinear algebra are powerful tools to cope with challenges arou...
International audienceIt has been shown that a best rank-R approximation of an order-k tensor may no...
International audienceThe concept of tensor rank, introduced in the twenties, has been popularized a...
© 1991-2012 IEEE. The widespread use of multisensor technology and the emergence of big data sets ha...
International audienceTensor decompositions are at the core of many Blind Source Separation (BSS) al...
International audienceTensors appear more and more often in signal processing problems, and especial...
Tensors, or multi-linear forms, are important objects in a variety of areas from analytics, to combi...
© 1991-2012 IEEE. Tensors or multiway arrays are functions of three or more indices (i,j,k,⋯)-simila...
The value of data cannot be underestimated in our current digital age. Data mining techniques have a...
International audienceThe concept of tensor rank was introduced in the twenties. In the seventies, w...
Multidimensional data, or tensors, arise natura lly in data analysis applications. Hitchcock&##39;s ...
We analyze data to build a quantitative understanding of the world. Linear algebra is the foundation...
The widespread use of multi-sensor technology and the emergence of big datasets has highlighted the ...
In many applications signals or data vary with respect to several parameters (such as spatial coord...
International audienceIs has been shown that a best rank-R approximation of an order-k tensor may no...
Tensor decomposition methods and multilinear algebra are powerful tools to cope with challenges arou...
International audienceIt has been shown that a best rank-R approximation of an order-k tensor may no...
International audienceThe concept of tensor rank, introduced in the twenties, has been popularized a...
© 1991-2012 IEEE. The widespread use of multisensor technology and the emergence of big data sets ha...