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>.
|Author||Daniel Falbel [aut, cre, cph], RStudio [cph], MADGRAD original implementation authors. [cph]|
|Maintainer||Daniel Falbel <firstname.lastname@example.org>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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