This article is cited in 2 scientific papers (total in 2 papers)
The structure of the Hessian and the efficient implementation of Newton's method in the problem of the canonical approximation of tensors
V. A. Kazeev, E. E. Tyrtyshnikov
Institute of Numerical Mathematics, Russian Academy of Sciences, ul. Gubkina 8, Moskow, 119333 Russia
A tensor given by its canonical decomposition is approximated by another tensor (again, in the canonical decomposition) of fixed lower rank. For this problem, the structure of the Hessian matrix of the objective function is analyzed. It is shown that all the auxiliary matrices needed for constructing the quadratic model can be calculated so that the computational effort is a quadratic function of the tensor dimensionality (rather than a cubic function as in earlier publications). An economical version of the trust region Newton method is proposed in which the structure of the Hessian matrix is efficiently used for multiplying this matrix by vectors and for scaling the trust region. At each step, the subproblem of minimizing the quadratic model in the trust region is solved using the preconditioned conjugate gradient method, which is terminated if a negative curvature direction is detected for the Hessian matrix.
tensor decompositions, canonical decomposition, low-rank approximations, trust region Newton method, conjugate gradient method.
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Computational Mathematics and Mathematical Physics, 2010, 50:6, 927–945
V. A. Kazeev, E. E. Tyrtyshnikov, “The structure of the Hessian and the efficient implementation of Newton's method in the problem of the canonical approximation of tensors”, Zh. Vychisl. Mat. Mat. Fiz., 50:6 (2010), 979–998; Comput. Math. Math. Phys., 50:6 (2010), 927–945
Citation in format AMSBIB
\by V.~A.~Kazeev, E.~E.~Tyrtyshnikov
\paper The structure of the Hessian and the efficient implementation of Newton's method in the problem of the canonical approximation of tensors
\jour Zh. Vychisl. Mat. Mat. Fiz.
\jour Comput. Math. Math. Phys.
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Gong X., Mohlenkamp M.J., Young T.R., “The Optimization Landscape For Fitting a Rank-2 Tensor With a Rank-1 Tensor”, SIAM J. Appl. Dyn. Syst., 17:2 (2018), 1432–1477
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