Transfer learning with many small datasets
I ended up doing what I proposed in the question: document(from customer X) -&gt; preprocessing(shared among customers) -&gt; feature extraction (shared among customers) -&gt; classification (specific to customer X). I had a loss for each customer X.
I trained the network with a custom training loop: https://keras.io/guides/writing_a_training_loop_from_scratch/
The training converged, which is what I was most uncertain about. The testing accuracy was a bit better compared to training the model with a single customer.
I still did not manage to find any papers on this topic though.