Performance-Enhancing Techniques for Tucker Tensor Decompositions in Data Processing KU Leuven
As datasets grow in size, so has their dimensionality in many cases. Numerical data in the form of arrays with 3 or more dimensions, i.e. tensors, are commonly found in hyperspectral imaging, diffusion tensor imaging, simulations, X-ray scans, and so on. Even relational databases can be represented using sparse tensors. As a result of this trend, tensor decompositions were developed to process such multidimensional numerical data. Among ...