Unverified50% confidenceFactExact time
An MLP is formed by stacking fully connected layers and can theoretically approximate continuous functions to arbitrary precision (universal approximation theorem), but training typically relies on large numbers of iterations and careful hyperparameter tuning, and the parameter count grows rapidly with hidden layer width.
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10/26/2026
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