scipy.optimize.LbfgsInvHessProduct

class scipy.optimize.LbfgsInvHessProduct(sk, yk)

Linear operator for the L-BFGS approximate inverse Hessian.

This operator computes the product of a vector with the approximate inverse of the Hessian of the objective function, using the L-BFGS limited memory approximation to the inverse Hessian, accumulated during the optimization.

Parameters:

sk : array_like, shape=(n_corr, n)

Array of n_corr most recent updates to the solution vector. (See [1]).

yk : array_like, shape=(n_corr, n)

Array of n_corr most recent updates to the gradient. (See [1]).

References

[R126]

Nocedal, Jorge. “Updating quasi-Newton matrices with limited storage.” Mathematics of computation 35.151 (1980): 773-782.

Attributes

H	Hermitian adjoint.
T	Transpose this linear operator.

Methods

__call__(x)
adjoint()	Hermitian adjoint.
dot(x)	Matrix-matrix or matrix-vector multiplication.
matmat(X)	Matrix-matrix multiplication.
matvec(x)	Matrix-vector multiplication.
rmatvec(x)	Adjoint matrix-vector multiplication.
todense()	Return a dense array representation of this operator.
transpose()	Transpose this linear operator.