Methods › General › Learning Rate Schedules › Polynomial Rate Decay

Polynomial Rate Decay

10 papers tagged archive 2025-07-28

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

Polynomial Rate Decay is a learning rate schedule where we polynomially decay the learning rate.

Papers archive 2025-07-28

10 shown of 10, 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

20 shown of 24 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
Semantic Segmentation5
Image Segmentation3
Object Detection3
Real-Time Object Detection3
Dichotomous Image Segmentation2
Image Classification2
Object2
Real-Time Semantic Segmentation2
Scene Parsing2
Segmentation2
Thermal Image Segmentation2
2D Semantic Segmentation1
3D Object Detection1
Attribute1
BIG-bench Machine Learning1
Computational Efficiency1
Data Augmentation1
General Classification1
Lesion Segmentation1
Medical Image Analysis1

Usage over time archive 2025-07-28

Papers per year tagged with Polynomial Rate Decay: 2016 to 2022, peak 3 3 0 2016: 3 papers 2016 2017: 1 paper 2017 2018: 2 papers 2018 2019: 2 papers 2019 2020: 1 paper 2020 2021: 0 papers 2021 2022: 1 paper 2022
Papers per year the archive tags with this method, by the paper's archive date (10 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

Learning Rate Schedules

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