Methods › General › Stochastic Optimization › Demon CM
Demon CM
Introduced by John Chen et al. in Demon: Improved Neural Network Training with Momentum Decay
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Demon CM, or SGD with Momentum and Demon, is the Demon momentum rule applied to SGD with momentum.
βₜ = βᵢₙᵢₜ·(1-t/T)/(1-βᵢₙᵢₜ) + βᵢₙᵢₜ(1-t/T)
θₜ₊₁ = θₜ - ηgₜ + βₜvₜ
vₜ₊₁ = βₜvₜ - ηgₜ
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Demon: Improved Neural Network Training with Momentum Decay 11 Oct 2019 · 2 repositories · arXiv:1910.04952
Tasks archive 2025-07-28
2 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Image Classification | 1 |
| image-classification | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections