Show how gradient descent can be used for learning a linear function that minimizes the absolute error.

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Show how gradient descent can be used for learning a linear function that minimizes the absolute error. [Hint: Do a case analysis of the error; for each example the absolute value is either the positive or the negative of the value.

What is appropriate when the value is zero?]

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