| Full text | |
| Author(s): |
Helou, Elias S.
;
Simoes, Lucas E. A.
Total Authors: 2
|
| Document type: | Journal article |
| Source: | INVERSE PROBLEMS; v. 33, n. 5 MAY 2017. |
| Web of Science Citations: | 1 |
| Abstract | |
This paper introduces and studies the convergence properties of a new class of explicit e-subgradient methods for the task of minimizing a convex function over a set of minimizers of another convex minimization problem. The general algorithm specializes to some important cases, such as first-order methods applied to a varying objective function, which have computationally cheap iterations. We present numerical experimentation concerning certain applications where the theoretical framework encompasses efficient algorithmic techniques, enabling the use of the resulting methods to solve very large practical problems arising in tomographic image reconstruction. (AU) | |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 11/02219-4 - New incremental methods for bi-level non-differentiable convex optimization with applications to image reconstruction for emission tomography |
| Grantee: | Lucas Eduardo Azevedo Simões |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 13/14615-7 - On the nonmonotone line search in gradient sampling methods for nonconvex and nonsmooth optimization |
| Grantee: | Lucas Eduardo Azevedo Simões |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 13/16508-3 - Fast computation of the generalized Backprojection operator with applications in tomographic image reconstruction |
| Grantee: | Elias Salomão Helou Neto |
| Support Opportunities: | Regular Research Grants |