cran
. See also theR-universe documentation.Package: stochQN 0.1.2-1
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, 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++.
Authors:
stochQN_0.1.2-1.tar.gz
stochQN_0.1.2-1.tar.gz(r-4.5-noble)stochQN_0.1.2-1.tar.gz(r-4.4-noble)
stochQN_0.1.2-1.tgz(r-4.4-emscripten)stochQN_0.1.2-1.tgz(r-4.3-emscripten)
stochQN.pdf |stochQN.html✨
stochQN/json (API)
# Install 'stochQN' in R: |
install.packages('stochQN', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/david-cortes/stochqn/issues
Last updated 3 years agofrom:c595f81ca7. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 16 2024 |
R-4.5-linux-x86_64 | OK | Nov 16 2024 |
Exports:adaQNadaQN_freeget_curr_xget_iteration_numberoLBFGSoLBFGS_freepartial_fitpartial_fit_logisticrun_adaQN_freerun_oLBFGS_freerun_SQN_freeSQNSQN_freestochastic.logistic.regressionupdate_funupdate_gradientupdate_hess_vec
Dependencies: