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AdaShift

4 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

AdaShift is a type of adaptive stochastic optimizer that decorrelates vₜ and gₜ in Adam by temporal shifting, i.e., using temporally shifted gradient gₜ₋ₙ to calculate vₜ. The authors argue that an inappropriate correlation between gradient gₜ and the second-moment term vₜ exists in Adam, which results in a large gradient being likely to have a small step size while a small gradient may have a large step size. The authors argue that such biased step sizes are the fundamental cause of non-convergence of Adam.

The AdaShift updates, based on the idea of temporal independence between gradients, are as follows:

gₜ = ∇fₜ(θₜ)

mₜ = ∑ⁿ⁻¹ᵢ₌₀βⁱ₁gₜ₋ᵢ/∑ⁿ⁻¹ᵢ₌₀βⁱ₁

Then for i=1 to M:

vₜ[i] = β₂vₜ₋₁[i] + (1-β₂)ϕ(g²ₜ₋ₙ[i])

θₜ[i] = θₜ₋₁[i] - αₜ/√(vₜ[i])·mₜ[i]

Source: AdaShift: Decorrelation and Convergence of Adaptive...See Code · MichaelKonobeev/adashift

Papers archive 2025-07-28

4 shown of 4, 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.

Tasks archive 2025-07-28

4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Image Classification1
Representation Learning1
Stochastic Optimization1
image-classification1

Usage over time archive 2025-07-28

Papers per year tagged with AdaShift: 2018 to 2024, peak 1 1 0 2018: 1 paper 2018 2019: 1 paper 2019 2020: 0 papers 2020 2021: 1 paper 2021 2022: 0 papers 2022 2023: 0 papers 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (4 dated). Bars are counts, not a trend claim.

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

Stochastic Optimization

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