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A regularized Newton method for the efficient approximation of tensors represented in the canonical tensor format

机译:用于规范张量格式表示的张量的有效逼近的正则化牛顿法

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In the present survey, we consider a rank approximation algorithm for tensors represented in the canonical format in arbitrary pre-Hilbert tensor product spaces. It is shown that the original approximation problem is equivalent to a finite dimensional ?_2 minimization problem. The ?_2 minimization problem is solved by a regularized Newton method which requires the computation and evaluation of the first and second derivative of the objective function. A systematic choice of the initial guess for the iterative scheme is introduced. The effectiveness of the approach is demonstrated in numerical experiments.
机译:在本次调查中,我们考虑在任意希尔伯特前张量乘积空间中以规范格式表示的张量的秩近似算法。结果表明,原始的近似问题等效于有限维的λ_2最小化问题。通过正则化的牛顿法来解决α_2最小化问题,该方法需要计算和评估目标函数的一阶和二阶导数。介绍了迭代方案初始猜测的系统选择。数值实验证明了该方法的有效性。

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