Package: stochQN
Type: Package
Title: Stochastic Limited Memory Quasi-Newton Optimizers
Version: 0.1.2-1
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>
URL: https://github.com/david-cortes/stochQN
BugReports: https://github.com/david-cortes/stochQN/issues
Description: 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++.
License: BSD_2_clause + file LICENSE
NeedsCompilation: yes
RoxygenNote: 6.1.1
Packaged: 2021-09-25 23:55:07 UTC; david
Repository: CRAN
Date/Publication: 2021-09-26 04:10:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-27 04:01:57 UTC; unix
Archs: stochQN.so.dSYM
