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) doi:10.48550/arXiv.2101.11075.
- Version0.1.0
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Last release05/10/2021
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Daniel Falbel
RStudio
Show author detailsRolesCopyright holderMADGRAD original implementation authors.
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