sgd: Stochastic Gradient Descent for Scalable Estimation

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.

AuthorDustin Tran [aut, cre], Panos Toulis [aut], Tian Lian [ctb], Ye Kuang [ctb], Edoardo Airoldi [ctb]
Date of publication2016-01-05 21:12:16
MaintainerDustin Tran <dustin@cs.columbia.edu>
LicenseGPL-2
Version1.1
https://github.com/airoldilab/sgd

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Files

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

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