Methods › General › Stochastic Optimization › AdaFisher
Adaptive Second Order Optimization via Fisher Information
AdaFisher
Introduced by Damien Martins Gomes et al. in AdaFisher: Adaptive Second Order Optimization via Fisher Information
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
AdaFisher – an adaptive second-order optimizer that leverages a block-diagonal approximation to the Fisher information matrix for adaptive gradient preconditioning.
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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Towards Practical Second-Order Optimizers in Deep Learning: Insights from Fisher Information Analysis 26 Apr 2025 · 1 repository · arXiv:2504.20096
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AdaFisher: Adaptive Second Order Optimization via Fisher Information 26 May 2024 · 1 repository · arXiv:2405.16397Syntology ran 7 of 10 samples · 3 unverified · 10 pointer-only (licence)
Tasks archive 2025-07-28
6 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 |
|---|---|
| Computational Efficiency | 2 |
| Image Classification | 2 |
| Language Modeling | 2 |
| Language Modelling | 2 |
| image-classification | 2 |
| Second-order methods | 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
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