Search for dissertations about: "Tensor matricization"

Found 2 swedish dissertations containing the words Tensor matricization.

  2. 1. Algorithms in data mining using matrix and tensor methods

    Author : Berkant Savas; Lars Eldén; Lieven De Lathauwer; Linköpings universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Volume; Minimization criterion; Determinant; Rank deficient matrix; Reduced rank regression; System identification; Rank reduction; Volume minimization; General algorithm; Handwritten digit classification; Tensors; Higher order singular value decomposition; Tensor approximation; Least squares; Tucker model; Multilinear algebra; Notation; Contraction; Tensor matricization; Newton s method; Grassmann manifolds; Product manifolds; Quasi-Newton algorithms; BFGS and L-BFGS; Symmetric tensor approximation; Local intrinsic coordinates; Global embedded coordinates; ; Numerical analysis; Numerisk analys;

    Abstract : In many fields of science, engineering, and economics large amounts of data are stored and there is a need to analyze these data in order to extract information for various purposes. Data mining is a general concept involving different tools for performing this kind of analysis. READ MORE

  4. 2. Identification and tuning of algorithmic parameters in parallel matrix computations : Hessenberg reduction and tensor storage format conversion

    Author : Mahmoud Eljammaly; Bo Kågström; Lars Karlsson; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES;

    Abstract : This thesis considers two problems in numerical linear algebra and high performance computing (HPC): (i) the parallelization of a new blocked Hessenberg reduction algorithm using Parallel Cache Assignment (PCA) and the tunability of its algorithm parameters, and (ii) storing and manipulating dense tensors on shared memory HPC systems.The Hessenberg reduction appears in the Aggressive Early Deflation (AED) process for identifying converged eigenvalues in the distributed multishift QR algorithm (state-of-the-art algorithm for computing all eigenvalues for dense square matrices). READ MORE