This survey provides an overview of higher-order tensor decompositions, their applications,
and available software. A tensor is a multidimensional or N-way array. Decompositions of …

In this paper, the term tensor refers simply to a multidimensional or N-way array, and we
consider how specially structured tensors allow for efficient storage and computation. First …

Tensors provide a generalized structure to store arbitrary indexable data, which is
applicable in fields such as chemometrics, physics simulations, signal processing and lies at …

Abstract Electrical Impedance Tomography (EIT) is an imaging technique that attempts to
reconstruct the conductivity distribution inside an object from electrical currents and …

In 1812, a French mathematician named Jacques Philippe Marie Binet pointed out several
important computations involved the multiplication of two matrices [53]. On November 30 of …

In recent times, multidimensional arrays are extensively used to handle large amount of data
in scientific research, engineering, and MOLAP applications. Most of the existing data …

Researchers from diverse disciplines are increasingly incorporating numeric high-order
data, ie, numeric tensors, within their practice. Just like the matrix-vector (MV) paradigm, the …

In this paper, we are interested in some front propagation problems coming from control
problems in d-dimensional spaces, with d≥ 2. As opposed to the usual level set method, we …

Degree of data sparsity increases with the increase of number of dimensions in high
performance scientific computing. Storing and applying operations on this highly sparse …

In this paper, we introduce data structures for storing the third derivative (tensor) of a
multivariate scalar function when the second and third derivatives of the function are sparse …