Although the bitter lesson suggests that end-to-end eventually wins, this talk observes that at a given level of (compute, data, algorithm, architecture), there exists an optimal structure to add to make things work at all. But we often forget to remove these when more end-to-end
Optimal Structure in End-to-End Learning: When to Remove Inductive Bias
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