Methods › General › Regularization › FIERCE

Feature Information Entropy Regularized Cross Entropy

FIERCE

7 papers tagged archive 2025-07-28

Introduced by Raphael Baena et al. in Preserving Fine-Grain Feature Information in Classification via Entropic Regularization

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

FIERCE is an entropic regularization on the feature space

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

17 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
Few-Shot Learning2
Blocking1
Classification1
Deep Learning1
Diversity1
Fault Diagnosis1
Fault localization1
Fine-Grained Image Classification1
Graph Attention1
Pose Estimation1
Position1
Position regression1
State Estimation1
Time Series1
Traffic Prediction1
Transfer Learning1
regression1

Usage over time archive 2025-07-28

Papers per year tagged with FIERCE: 2022 to 2025, peak 3 3 0 2022: 1 paper 2022 2023: 3 papers 2023 2024: 0 papers 2024 2025: 3 papers 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

Regularization

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