Stochastic Limited Memory Quasi-Newton Optimizers R package stochQN version 0.1.2-1 CRAN Task View: Optimization (https://CRAN.R-project.org/view=Optimization) 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++. Software David Cortes <david.cortes.rivera@gmail.com> Comprehensive R Archive Network (CRAN) David Cortes BSD_2_clause + file LICENSE (https://CRAN.R-project.org/package=stochQN/LICENSE) 2021-09-26 application/tgz https://CRAN.R-project.org/package=stochQN doi:10.32614/CRAN.package.stochQN