Implementations of stochastic, limitedmemory quasiNewton optimizers, similar in spirit to the LBFGS (Limitedmemory BroydenFletcherGoldfarbShanno) 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 quasiNewton) (Byrd, R.H., Hansen, S.L., Nocedal, J. and Singer, Y., 2016 <arXiv:1401.7020>), adaQN (adaptive quasiNewton) (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++.
Package details 


Author  David Cortes 
Maintainer  David Cortes <[email protected]> 
License  BSD_2_clause + file LICENSE 
Version  0.1.2 
URL  https://github.com/davidcortes/stochQN 
Package repository  View on CRAN 
Installation 
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