Comment on Every Model Learned by Gradient Descent Is Approximately a Kernel MachineparentComments−eugenhotaj5yFair enough, but the number of support vectors for non trivial problems is still pretty large (as I understand but could be wrong), e.g. 20-30% of the dataset. Having to iterate over 30% of say imagenet on each batch of predictions seems unfeasible.
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Fair enough, but the number of support vectors for non trivial problems is still pretty large (as I understand but could be wrong), e.g. 20-30% of the dataset. Having to iterate over 30% of say imagenet on each batch of predictions seems unfeasible.