Methods › General › Stochastic Optimization › Polyak Averaging
Polyak Averaging
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Polyak Averaging is an optimization technique that sets final parameters to an average of (recent) parameters visited in the optimization trajectory. Specifically if in t iterations we have parameters θ₁, θ₂, …, θₜ, then Polyak Averaging suggests setting
θₜ =1/t∑ᵢθᵢ
Image Credit: Shubhendu Trivedi & Risi Kondor
Papers archive 2025-07-28
3 shown of 3, 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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Statistical Inference for Online Algorithms 22 May 2025 · 1 repository · arXiv:2505.17300
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Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells 25 Oct 2018 · 4 repositories · arXiv:1810.10804
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Going Deeper with Convolutions 17 Sep 2014 · 83 repositories · arXiv:1409.4842Syntology ran 27 of 42 samples · 15 unverified · 20 pointer-only (licence)
Tasks archive 2025-07-28
18 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
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