How transferable are features in deep neural networks? - Yosinski et al.
- Train on a base network, try to take that network and tweak it to work for a new target network.
- Notes from CS231N.
Tries to figure out how much information can we transfer between networks trained on different datasets.
Quantifies the transferability by layer.
- First few layers are general (Gabor Filters kind of features) and can adapt well.