Methods › General › Structured Prediction › LTLS
Log-time and Log-space Extreme Classification
LTLS
Introduced by Kalina Jasinska et al. in Log-time and Log-space Extreme Classification
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
LTLS is a technique for multiclass and multilabel prediction that can perform training and inference in logarithmic time and space. LTLS embeds large classification problems into simple structured prediction problems and relies on efficient dynamic programming algorithms for inference. It tackles extreme multi-class and multi-label classification problems where the size C of the output space is extremely large.
Papers archive 2025-07-28
2 shown of 2, 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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Efficient Loss-Based Decoding on Graphs For Extreme Classification 8 Mar 2018 · 1 repository · arXiv:1803.03319Syntology ran 0 of 4 samples · 4 unverified
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Log-time and Log-space Extreme Classification 7 Nov 2016 · 1 repository · arXiv:1611.01964Syntology ran 0 of 7 samples · 7 unverified
Tasks archive 2025-07-28
4 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 |
|---|---|
| Classification | 2 |
| General Classification | 2 |
| Prediction | 1 |
| Structured Prediction | 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