david-cortes/stochQN: Stochastic Limited Memory Quasi-Newton Optimizers

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, Yu, Guenter, (2007) <http://proceedings.mlr.press/v2/schraudolph07a.html>), SQN (stochastic quasi-Newton) (Byrd, Hansen, Nocedal, Singer, (2016) <arXiv:1401.7020>), adaQN (adaptive quasi-Newton) (Keskar, Berahas (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++.

install.packages("remotes")
remotes::install_github("david-cortes/stochQN")