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Agreed, also this model fully uses the other images, just not the way that traditional supervised learning would. With "just 10 labels" is more accurate. Impres
by colincooke 7y ago
Agreed, also this model fully uses the other images, just not the way that traditional supervised learning would. With "just 10 labels" is more accurate. Impressive results, but this isn't some hyper-convergence technique that somehow trains on only ten images.
- mattkrause 7y agoThis depends a lot on the application. It seems like a big win for images and other stuff where getting images is cheap, but labelling them is expensive. Less great for (say) drug discovery where running the experiments to generate the data points is the bottleneck.