update_gradient

A free-mode optimizer from this package (`oLBFGS_free`, `SQN_free`, `adaQN_free`) which
after the last run had requested a new gradient evaluation..

optimizer

The (expected value of the) gradient as evaluated on the values of `x` that
were returned in the request. Must be a numeric vector.

gradient

Update the (expected) gradient in an optimizer from this package, 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_gradient: Update gradient (oLBFGS, SQN, adaQN)

Description

Usage

Arguments

Value