A CMA-ES plus attention-pruning training algorithm for block optical neural networks prunes 60-80% of parameters with under 5% accuracy loss and shows improved noise robustness.
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Efficient training for large-scale optical neural network using an evolutionary strategy and attention pruning
A CMA-ES plus attention-pruning training algorithm for block optical neural networks prunes 60-80% of parameters with under 5% accuracy loss and shows improved noise robustness.