Widrow–Hoff learning rule

E1721535 UNEXPLORED

The Widrow–Hoff learning rule is a foundational adaptive algorithm for training linear neurons and perceptrons by iteratively minimizing the mean squared error between desired and actual outputs.

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Label	Occurrences
Widrow–Hoff learning rule canonical	2

Referenced by (2)

Full triples — surface form annotated when it differs from this entity's canonical label.

Bernard Widrow → knownFor → Widrow–Hoff learning rule ⓘ

Bernard Widrow → coInvented → Widrow–Hoff learning rule ⓘ