What is it?
: the function never changes faster than rate . When the gradient is -Lipschitz, gradient descent with step is guaranteed to decrease the loss.
Formulas
- descent lemma
Where it shows up in AI
The safe learning rate is set by the Lipschitz constant of the gradient: .
Wasserstein GANs require a 1-Lipschitz critic, enforced by weight clipping, gradient penalties or spectral normalization.
Where is it used?
Computing topics reachable from here, through the chain of ideas that leads to them:
⚛ Physics and simulation
- Initial value problems: existence and uniqueness→Physics engines★★★★★
- Initial value problems: existence and uniqueness→Physics engines→N-body gravitational simulation★★★★★
- Initial value problems: existence and uniqueness→Physics engines→Fluid dynamics and CFD★★★★★
- Initial value problems: existence and uniqueness→Physics engines→Fluid dynamics and CFD→Weather and climate modelling★★★★★
What depends on it
This page has the essentials. A fuller treatment (intuition, formal definition, worked example) is on the way.