New notes on using ML to generalize from small amounts of training data: attacking MNIST with just 10 training examples for each digit. 93.81% accuracy: http://cognitivemedium.com/rmnist_anneal_ensemble …
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I had a question on the ensemble. The way I was taught it, the ensemble performs best when the models it averages are really different but aren't you using covnets all the way through?
Yes, I am. It'd be nice to find other models with pretty good performance to include in the ensemble.
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so then you are just averaging covnets with different hyperparameters?
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No, with the same hyperparameters. (This is not uncommon.) The difference that arises is due to differences in initial weights. Using different convnets with different hps would certainly be worthwhile, but I haven't done it.
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