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A comment on Coding the History of Deep Learning. Parent comment
matrix inversion is ~O(n^3)
gradient descent is ~O(np) where p is the number of predictors and n are the observations (n x p matrix).
for lasso, calculating that derivative of the multiplier is not possible (for all points), so coordinated descent is used.
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matrix inversion is ~O(n^3)
gradient descent is ~O(np) where p is the number of predictors and n are the observations (n x p matrix).
for lasso, calculating that derivative of the multiplier is not possible (for all points), so coordinated descent is used.