Computational mathematicians finalized algorithms that treated neural network architectural hyperparameters as continuous mathematical variables, allowing deep learning models to automatically tune their own internal training rules during backpropagation.
Part of the 32 AI Roots Facts: 2016 Edition archive. HistoricallyVerified
Top 5 Structural Foundations: Origins
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