Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1142873 | Operations Research Letters | 2010 | 6 Pages |
Abstract
We introduce a first-order Mirror-Descent (MD) type algorithm for solving nondifferentiable convex problems having a combination of simple constraint set XX (ball, simplex, etc.) and an additional functional constraint. The method is tuned to exploit the structure of XX by employing an appropriate non-Euclidean distance-like function. Convergence results and efficiency estimates are derived. The performance of the algorithm is demonstrated by solving certain image deblurring problems.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Discrete Mathematics and Combinatorics
Authors
Amir Beck, Aharon Ben-Tal, Nili Guttmann-Beck, Luba Tetruashvili,