Name
Abstract | ||
|---|---|---|
In this article we present a framework for line search methods for optimization on smooth homogeneous manifolds, with particular emphasis to the Lie group of real orthogonal matrices. We propose strategies of univariate descent (UVD), methods. The main advantage of this approach is that the optimization problem is broken down into one-dimensional optimization problems, so that each optimization step involves little computation effort. In order to assess its numerical performance, we apply the devised method to eigen-problems as well as to independent component analysis in signal processing. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.matcom.2008.03.013 | Mathematics and Computers in Simulation |
Keywords | Field | DocType |
independent component analysis,signal processing,eigen-problems,line search method,particular emphasis,lie group actions,computation effort,numerical performance,main advantage,one-dimensional optimization problem,optimization step,optimization problem,lie group,homogeneous manifold,optimization on manifolds,descent method,line search | Continuous optimization,Orthogonal matrix,Mathematical optimization,Derivative-free optimization,Vector optimization,Line search,Random optimization,Optimization problem,Mathematics,Manifold | Journal |
Volume | Issue | ISSN |
79 | 4 | Mathematics and Computers in Simulation |
Citations | PageRank | References |
9 | 0.70 | 18 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Elena Celledoni | 1 | 171 | 34.40 |
| Simone Fiori | 2 | 494 | 52.86 |