Projected Gradient Algorithm
Oct 23, 2020 · Q(:) is a function from Rnto Rn, and itself is an optimization problem: P Q(x 0) = argmin x2Q 1 2 kx x 0k2 2: I PGD is an \economic" algorithm if the problem is easy to solve. This is not true for general Qand there are lots of constraint sets that are very di cult to project onto. I If Qis a convex set, the optimization problem has a unique ...
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