Methods › General › Robust Training › ELR

Early Learning Regularization

ELR

7 papers tagged archive 2025-07-28

Introduced by Sheng Liu et al. in Early-Learning Regularization Prevents Memorization of Noisy Labels

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

The archive carries no description for this method.

PaperSource

Papers archive 2025-07-28

7 shown of 7, 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 26 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
Active Learning2
Classification2
General Classification2
Memorization2
Diversity1
Image Classification1
Learning with noisy labels1
Low Resource Neural Machine Translation1
Low-Resource Neural Machine Translation1
Machine Translation1
Medical Image Segmentation1
NMT1
Object1
Object Detection1
Re-Ranking1
Segmentation1
Semantic Segmentation1
Sentence1
Text Classification1
Transfer Learning1

Usage over time archive 2025-07-28

Papers per year tagged with ELR: 2020 to 2025, peak 3 3 0 2020: 2 papers 2020 2021: 3 papers 2021 2022: 1 paper 2022 2023: 0 papers 2023 2024: 0 papers 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (7 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

Robust Training

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