Oja's rule

Deleting two terms from the tied-SAE gradient leaves the Oja update

A LessWrong post shows the Oja rule falling out of tied sparse-autoencoder descent once two terms are dropped, then reports a language-model test where an initialization change moved the backprop baseline more than the Hebbian gap it was meant to explain.