update_hess_vec

An `SQN_free` optimizer which after the last run had requested a new Hessian-vector evaluation.

optimizer

The (expected) value of the Hessian evaluated at the values of `x` that were returned in the
request, multiplied by the vector that was returned in the same request. Must be a numeric vector.

hess_vec

Update the (expected) values of the Hessian-vector product in an `SQN_free` object,
after it has been requested by the optimizer (do NOT update it otherwise).

Implementations of stochastic, limited-memory quasi-Newton optimizers,
similar in spirit to the LBFGS (Limited-memory Broyden-Fletcher-Goldfarb-Shanno) algorithm,
for smooth stochastic optimization. Implements the following methods:
oLBFGS (online LBFGS) (Schraudolph, N.N., Yu, J. and Guenter, S., 2007 <http://proceedings.mlr.press/v2/schraudolph07a.html>),
SQN (stochastic quasi-Newton) (Byrd, R.H., Hansen, S.L., Nocedal, J. and Singer, Y., 2016 <arXiv:1401.7020>),
adaQN (adaptive quasi-Newton) (Keskar, N.S., Berahas, A.S., 2016, <arXiv:1511.01169>).
Provides functions for easily creating R objects
with partial_fit/predict methods from some given objective/gradient/predict functions.
Includes an example stochastic logistic regression using these optimizers.
Provides header files and registered C routines for using it directly from C/C++.

update_hess_vec: Update Hessian-vector product (SQN)

Description

Usage

Arguments

Value