|View source on GitHub|
Returns cholesky of chol @ chol.T + multiplier * u @ u.T.
tfp.experimental.substrates.numpy.math.cholesky_update( chol, update_vector, multiplier=1.0, name=None )
Given a (batch of) lower triangular cholesky factor(s)
chol, along with a
(batch of) vector(s)
update_vector, compute the lower triangular cholesky
factor of the rank-1 update
chol @ chol.T + multiplier * u @ u.T, where
multiplier is a (batch of) scalar(s).
chol has shape
[L, L], this has complexity
O(L^2) compared to the
naive algorithm which has complexity
||Optional name for this op.|
 Oswin Krause. Christian Igel. A More Efficient Rank-one Covariance Matrix Update for Evolution Strategies. 2015 ACM Conference. https://www.researchgate.net/publication/300581419_A_More_Efficient_Rank-one_Covariance_Matrix_Update_for_Evolution_Strategies