Description Usage Arguments Value
Gradient of Bregman Loss in Gaussian Case with respect to v
1 | gaussian_grad_v(x, a, v, s, lambda, mu0)
|
x |
A single row of column of x, for which we want to minimize distance to the mean. |
a |
Either a vector or scale representing the latent scores. |
v |
Either a vector or scale representing the latent loadings. |
s |
Either the s^th row or column of the matrix AV^T - a_cv_c^T |
lambda |
The regularization parameter in the optimization. |
mu0 |
The value to regularize towards. |
The value of the gradient of the bregman loss with respect to the parameter v.
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