SetThe gradient has Lipschitz continuity with constantwhere the norm is the spectral norm. The proximal gradient method is thereforeFor , part d makes the second step explicit:where is the capped simplex; when , this proximal step is the identity.
A standard fixed choice is ; the wider interval also gives convergence under the usual forward-backward conditions. For a general convex objective, the function-value error is . If has full column rank, the quadratic term is strongly convex and an appropriate fixed step gives a linear convergence rate.
Articles by others on the same topic
There are currently no matching articles.