# Bibliography

Conference Paper (international conference)

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

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**: **2013 IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2013, p. 5964-5968

**: **IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP 2013,
(Vancouver, CA, 27.05.2013-31.05.2013)

**: **GA102/09/1278, GA ČR

**: **tensor factorization,
Gauss-Newton method

**(eng): **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 approximate Hessian for the problem. It is shown that the inversion can be computed on O(NR^6) operations, where N and R is the tensor order and rank, respectively. It is less than in the best existing state-of-the art algorithm with O(N^3R^6) operations. The damped Gauss-Newton algorithm is suitable namely for difficult scenarios, where nearly-colinear factors appear in several modes simultaneously. Performance of the method is shown on decomposition of large tensors (100 × 100 × 100 and 100 × 100 × 100 × 100) of rank 5 to 90.

**: **BB