Natural Gradient
Definition
The natural gradient takes into account the geometry of the model distribution during learning.
An optimization direction that scales the ordinary gradient by the geometry of the model distribution, often via the Fisher information.
Simply explained
The next learning step is guided by how strongly it changes the model behavior.
Why it matters in practice
Helps realistically assess model quality, limits, and technical decisions.
Example from business
A policy optimizer limits changes relative to the distribution geometry rather than only in parameter space.
Limits and pitfalls
- Do not confuse with normalized gradient or ignore matrix approximations.
Origin & history
Amari formulated the Natural Gradient in information geometry.
Use in mid-sized companies
- Possible application: A policy optimizer limits changes relative to the distribution geometry rather than only in parameter space.
Frequently asked questions
What does Natural Gradient mean?
An optimization direction that scales the ordinary gradient by the geometry of the model distribution, often via the Fisher information.
Which mistakes should be avoided?
Do not confuse with normalized gradient or ignore matrix approximations.
Sources
Source checked on 10.10.2026. Editorial application examples are hypothetical; no evidence of real customer results.
Editorially reviewed on: