ml-recall

Optimization & Calculus

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Let us say that we have computed the gradient of our cost function and stored it in a vector $g$ . The model has $D$ parameters and is trained on $N$ examples. What is the cost of one gradient descent update given the gradient?

$O(D)$ 1
$O(N)$ 2
$O(ND)$ 3
$O(ND^2)$ 4

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