How far are biologically-plausible local learning rules from backpropagation (BP)?
In our new ICML paper we look at local self-supervised learning and find how to better align its gradients to BP.
We achieve competitive performance on various datasets!
GerstnerLab
Can we match self-supervised backpropagation using local learning rules? We show it is possible in our new paper accepted by ICML. We achieve:
1. theoretical equivalence to BP in a controlled setup
2. new SOTA for local learning across image datasets
3. same performance as BP on multiple datasets
