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madgrad  

'MADGRAD' Method for Stochastic Optimization
View on CRAN: Click here


Download and install madgrad package within the R console
Install from CRAN:
install.packages("madgrad")

Install from Github:
library("remotes")
install_github("cran/madgrad")

Install by package version:
library("remotes")
install_version("madgrad", "0.1.0")



Attach the package and use:
library("madgrad")
Maintained by
Daniel Falbel
[Scholar Profile | Author Map]
First Published: 2021-05-10
Latest Update: 2021-05-10
Description:
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) .
How to cite:
Daniel Falbel (2021). madgrad: 'MADGRAD' Method for Stochastic Optimization. R package version 0.1.0, https://cran.r-project.org/web/packages/madgrad. Accessed 31 Mar. 2025.
Previous versions and publish date:
No previous versions
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View madgrad citation profile
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Complete documentation for madgrad
Functions, R codes and Examples using the madgrad R package
Some associated functions: optim_madgrad . 
Some associated R codes: madgrad.R .  Full madgrad package functions and examples
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