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Stability analysis and fast damped-gauss-newton algorithm for INDSCAL tensor decomposition

机译:INDSCAL张量分解的稳定性分析和快速阻尼高斯牛顿算法

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INDSCAL is a special case of the CANDECOMP-PARAFAC (CP) decomposition of three or more-way tensors, where two factor matrices are equal. This paper provides a stability analysis of INDSCAL that is done by deriving the Cramér-Rao lower bound (CRLB) on variance of an unbiased estimate of the tensor parameters from its noisy observation (the tensor plus an i.i.d. Gaussian random tensor). The existence of the bound reveals necessary conditions for the essential uniqueness of the INDSCAL decomposition. This is compared with previous results on CP. Next, analytical expressions for the inverse of the Hessian matrix, which is needed to compute the CRLB, are used in a damped Gaussian (Levenberg-Marquardt) algorithm, which gives a novel method for INDSCAL having a lower computational complexity.
机译:INDSCAL是三个或更多方向张量的CANDECOMP-PARAFAC(CP)分解的特例,其中两个因子矩阵相等。本文提供了一种INDSCAL的稳定性分析方法,该方法是通过从嘈杂的观测值(张量加上i.d.高斯随机张量)得出的张量参数的无偏估计的方差中得出Cramér-Rao下界(CRLB)来完成的。边界的存在为INDSCAL分解的本质唯一性揭示了必要的条件。将其与CP上的先前结果进行比较。接下来,在阻尼高斯(Levenberg-Marquardt)算法中使用了计算CRLB所需的Hessian矩阵逆的解析表达式,这为INDSCAL提供了一种具有较低计算复杂度的新颖方法。

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