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AdaSqrt

1 paper tagged archive 2025-07-28

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

AdaSqrt is a stochastic optimization technique that is motivated by the observation that methods like Adagrad and Adam can be viewed as relaxations of Natural Gradient Descent.

The updates are performed as follows:

t ←t + 1

αₜ ←√(t)

gₜ ←∇_θf(θₜ₋₁)

Sₜ ←Sₜ₋₁ + gₜ²

θₜ₊₁ ←θₜ + ηαₜgₜ/(Sₜ + ϵ)

Source: Second-order Information in First-order Optimization Methods

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.

Tasks archive 2025-07-28

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

TaskPapers
2D Human Pose Estimation1

Usage over time archive 2025-07-28

Papers per year tagged with AdaSqrt: 2019 to 2019, peak 1 1 0 2019: 1 paper 2019
Papers per year the archive tags with this method, by the paper's archive date (1 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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