Sometimes to solve a constrained optimization problem, projected gradient descent algorithm is used. Since the projection to a constraint set is some function, one might think it is needed to compute the gradient of this projection function via chain rule/backprop once applying the projection. This is not right, but can someone give some intuition or rigorous reasoning why?
2026-03-24 22:08:23.1774390103
gradient of projection operator in projected gradient descent
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