Journal
INVERSE PROBLEMS
Volume 27, Issue 10, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/0266-5611/27/10/105008
Keywords
-
Categories
Funding
- SCAT (Support Center for Advanced Telecommunications)
- JSPS [09J09539]
- Grants-in-Aid for Scientific Research [09J09539] Funding Source: KAKEN
Ask authors/readers for more resources
In this paper, we present an over-relaxed variant of the fast iterative shrinkage-thresholding algorithm (FISTA)/the monotone FISTA (MFISTA). FISTA and MFISTA are iterative first-order algorithms, whose convergence rates of the objective function are O(1/k(2)) for an iteration counter k, for the minimization of the sum of a smooth and a nonsmooth convex function. FISTA and MFISTA are composed of the forward-backward splitting step together with a certain computationally efficient shifting step. The stepsize available in the forward-backward splitting step in these algorithms has been limited to a fixed value determined by the Lipschitz constant of the gradient of the smooth function. Examples of the proposed scheme admit variable stepsizes in broader ranges than FISTA/MFISTA, while keeping the same convergence rate O(1/k(2)). A numerical example in a well-conditioned case demonstrates the effect of the proposed relaxations by showing that the proposed scheme outperforms, in the speed of convergence, the original FISTA and MFISTA.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available