Methods › General › Loss Functions › HAPPIER
Hierarchical Average Precision training for Pertinent ImagE Retrieval
HAPPIER
Introduced by Elias Ramzi et al. in Hierarchical Average Precision Training for Pertinent Image Retrieval
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The archive carries no description for this method.
Papers archive 2025-07-28
5 shown of 5, 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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The pursuit of happiness 12 Jun 2025 · 0 repositories · arXiv:2506.10537
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Finding Beautiful and Happy Images for Mental Health and Well-being Applications 28 Apr 2024 · 0 repositories · arXiv:2404.18109
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Income and emotional well-being: Evidence for well-being plateauing around $200,000 per year 2 Dec 2023 · 0 repositories · arXiv:2401.05347
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Neural Mixed Effects for Nonlinear Personalized Predictions 13 Jun 2023 · 1 repository · arXiv:2306.08149
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Hierarchical Average Precision Training for Pertinent Image Retrieval 5 Jul 2022 · 2 repositories · arXiv:2207.04873Syntology ran 6 of 9 samples · 3 unverified
Tasks archive 2025-07-28
2 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Image Retrieval | 1 |
| Metric Learning | 1 |
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