Package: madgrad 0.1.0

madgrad: 'MADGRAD' Method for Stochastic Optimization

A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization algorithm. MADGRAD is a 'best-of-both-worlds' optimizer with the generalization performance of stochastic gradient descent and at least as fast convergence as that of Adam, often faster. A drop-in optim_madgrad() implementation is provided based on Defazio et al (2020) <arxiv:2101.11075>.

Authors:Daniel Falbel [aut, cre, cph], RStudio [cph], MADGRAD original implementation authors. [cph]

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madgrad.pdf |madgrad.html✨
madgrad/json (API)

# Install 'madgrad' in R:
install.packages('madgrad', repos = c('https://dfalbel.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 8 scripts 136 downloads 1 exports 18 dependencies

Last updated 4 years agofrom:40be6a66fe. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winNOTENov 16 2024
R-4.5-linuxNOTENov 16 2024
R-4.4-winNOTENov 16 2024
R-4.4-macNOTENov 16 2024
R-4.3-winNOTENov 16 2024
R-4.3-macNOTENov 16 2024

Exports:optim_madgrad

Dependencies:bitbit64callrclicorodescellipsisgluejsonlitemagrittrprocessxpsR6Rcpprlangsafetensorstorchwithr