Article ID Journal Published Year Pages File Type
1142873 Operations Research Letters 2010 6 Pages PDF
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.

Related Topics
Physical Sciences and Engineering Mathematics Discrete Mathematics and Combinatorics
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