sgd: Stochastic Gradient Descent for Scalable Estimation

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A fast and flexible set of tools for large scale estimation. It features many stochastic gradient methods, built-in models, visualization tools, automated hyperparameter tuning, model checking, interval estimation, and convergence diagnostics.

Author
Dustin Tran [aut, cre], Panos Toulis [aut], Tian Lian [ctb], Ye Kuang [ctb], Edoardo Airoldi [ctb]
Date of publication
2016-01-05 21:12:16
Maintainer
Dustin Tran <dustin@cs.columbia.edu>
License
GPL-2
Version
1.1
URLs

View on CRAN

Man pages

plot.sgd
Plot objects of class 'sgd'.
predict.sgd
Predict for objects of class 'sgd'
print.sgd
Print objects of class 'sgd'.
sgd
Stochastic gradient descent
winequality
Wine quality data of white wine samples from Portugal

Files in this package

sgd
sgd/inst
sgd/inst/doc
sgd/inst/doc/sgd-jss.pdf.asis
sgd/inst/doc/sgd-jss.pdf
sgd/tests
sgd/tests/testthat.R
sgd/tests/testthat
sgd/tests/testthat/test-linear.R
sgd/tests/testthat/test-lasso.R
sgd/src
sgd/src/Makevars
sgd/src/sgd
sgd/src/sgd/base_sgd.h
sgd/src/sgd/explicit_sgd.h
sgd/src/sgd/momentum_sgd.h
sgd/src/sgd/nesterov_sgd.h
sgd/src/sgd/implicit_sgd.h
sgd/src/validity-check
sgd/src/validity-check/cox_validity_check_model.h
sgd/src/validity-check/glm_validity_check_model.h
sgd/src/validity-check/validity_check.h
sgd/src/validity-check/m_validity_check_model.h
sgd/src/validity-check/gmm_validity_check_model.h
sgd/src/post-process
sgd/src/post-process/gmm_post_process.h
sgd/src/post-process/glm_post_process.h
sgd/src/post-process/cox_post_process.h
sgd/src/post-process/m_post_process.h
sgd/src/learn-rate
sgd/src/learn-rate/learn_rate_value.h
sgd/src/learn-rate/base_learn_rate.h
sgd/src/learn-rate/onedim_eigen_learn_rate.h
sgd/src/learn-rate/ddim_learn_rate.h
sgd/src/learn-rate/onedim_learn_rate.h
sgd/src/sgd.cpp
sgd/src/data
sgd/src/data/data_set.h
sgd/src/data/data_point.h
sgd/src/model
sgd/src/model/gmm_model.h
sgd/src/model/glm_model.h
sgd/src/model/base_model.h
sgd/src/model/cox_model.h
sgd/src/model/glm
sgd/src/model/glm/glm_family.h
sgd/src/model/glm/glm_transfer.h
sgd/src/model/m_model.h
sgd/src/model/m-estimation
sgd/src/model/m-estimation/m_loss.h
sgd/src/basedef.h
sgd/src/Makevars.win
sgd/src/RcppExports.cpp
sgd/NAMESPACE
sgd/demo
sgd/demo/glm-poisson-regression.R
sgd/demo/bench-corr-linear-regression.R
sgd/demo/normal-method-of-moments.R
sgd/demo/linear-regression.R
sgd/demo/cox-regression.R
sgd/demo/m-estimation.R
sgd/demo/glm-logistic-regression.R
sgd/demo/00Index
sgd/demo/bench-linear-regression.R
sgd/demo/bench-logistic-wine.R
sgd/data
sgd/data/winequality.rda
sgd/R
sgd/R/sgd.R
sgd/R/data-winequality.R
sgd/R/print.sgd.R
sgd/R/RcppExports.R
sgd/R/plot.sgd.R
sgd/R/predict.sgd.R
sgd/vignettes
sgd/vignettes/sgd-jss.pdf.asis
sgd/README.md
sgd/MD5
sgd/build
sgd/build/vignette.rds
sgd/DESCRIPTION
sgd/man
sgd/man/print.sgd.Rd
sgd/man/plot.sgd.Rd
sgd/man/winequality.Rd
sgd/man/sgd.Rd
sgd/man/predict.sgd.Rd