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37 (0,106s)

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Deflation Method for CANDECOMP/PARAFAC Tensor Decomposition

CANDECOMP/PARAFAC tensor decomposition (CPD) approximates multiway data by rank-1 tensors. Unlike matrix decomposition, the procedure which estimates the best rank-R tensor approximation through R sequential best rank-1 approximatio...

BB - Aplikovaná statistika, operační výzkum

  • 2014
  • D
  • Link
Result

Stability of CANDECOMP-PARAFAC tensor decomposition

In this paper, stability of the CANDECOMP-PARAFAC (CP) tensor decomposition is addressed. It is done by deriving the Cramer-Rao lower bound (CRLB) on variance of an unbiased estimate of the tensor parameters, i.e. elements of its fa...

BB - Aplikovaná statistika, operační výzkum

  • 2011
  • D
Result

Rank Splitting for CANDECOMP/PARAFAC

CANDECOMP/PARAFAC (CP) approximates multiway data by a sum of rank-1 tensors. Our recent study has presented a method to rank-1 tensor deflation, i.e. sequential extraction of rank-1 tensor components. In this paper, we extend the m...

BB - Aplikovaná statistika, operační výzkum

  • 2015
  • D
  • Link
Result

Tensor Deflation for CANDECOMP/PARAFAC - Part II: Initialization and Error Analysis

In Part I of the study of the tensor deflation for CANDECOMP/PARAFAC, we have shown that the rank-1 tensor de- flation is applicable under some conditions. Part II of the study presents several initialization algorithms suitable for...

BB - Aplikovaná statistika, operační výzkum

  • 2015
  • Jx
  • Link
Result

A Further Improvement of a Fast Damped Gauss?Newton Algorithm for CANDECOMP-PARAFAC Tensor Decomposition

In this paper, a novel implementation of the damped Gauss-Newton algorithm (also known as Levenberg-Marquart) for the CANDECOMP-PARAFAC (CP) tensor decomposition is proposed. The method is based on a fast inversion of the approximat...

BB - Aplikovaná statistika, operační výzkum

  • 2013
  • D
Result

Cramér-Rao-Induced Bounds for CANDECOMP/ PARAFAC Tensor Decomposition

This paper presents a Cramér-Rao lower bound (CRLB) on the variance of unbiased estimates of factor matrices in Canonical Polyadic (CP) or CANDECOMP/PARAFAC (CP) decompositions of a tensor from noisy observations, (i.e., the tensor ...

BB - Aplikovaná statistika, operační výzkum

  • 2013
  • Jx
  • Link
Result

Probabilistic inference with noisy-threshold models based on a CP tensor decomposition

. Such decomposition is referred to as Canonical Polyadic (CP)or CANDECOMP-PARAFAC (CP...

JD - Využití počítačů, robotika a její aplikace

  • 2014
  • Jx
  • Link
Result

CANDECOMP/PARAFAC Decomposition of High-Order Tensors Through Tensor Reshaping

In general, algorithms for order-3 CANDECOMP/ PARAFAC (CP), also coined canonical polyadic decomposition (CPD), are easy to implement and can be extended to higher order CPD. Unfortunately, the algorithms become computationally dema...

BB - Aplikovaná statistika, operační výzkum

  • 2013
  • Jx
  • Link
Result

Low Complexity Damped Gauss-Newton algorithms for CANDECOMP/PARAFAC

The damped Gauss-Newton (dGN) algorithm for CANDECOMP/PARAFAC (CP) decomposition can handle the challenges of factors and different magnitudes of factors; nevertheless, for factorization of an order-N tensor of size I_1I_2 I_N with ...

BB - Aplikovaná statistika, operační výzkum

  • 2013
  • Jx
  • Link
Result

Fast Alternating LS Algorithms for High Order CANDECOMP/PARAFAC Tensor Factorizations

CANDECOMP/PARAFAC (CP) has found numerous applications in wide variety of areas such as in chemometrics, telecommunication, data mining, neuroscience, separated representations. For an order- tensor, most CP algorithms can be comput...

BB - Aplikovaná statistika, operační výzkum

  • 2013
  • Jx
  • Link
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