arXiv · 1801.02509
Convergence rates of proximal gradient methods via the convex conjugate
Abstract
We give a novel proof of the $O(1/k)$ and $O(1/k^2)$ convergence rates of the proximal gradient and accelerated proximal gradient methods for composite convex minimization. The crux of the new proof is an upper bound constructed via the convex conjugate of the objective function.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
David H. Gutman, Javier F. Pena. 2018-01-09. Convergence rates of proximal gradient methods via the convex conjugate. https://arxiv.org/abs/1801.02509
Cite the original work for its findings. Save a collection to share your selection of sources.