Name
Abstract | ||
|---|---|---|
In the present paper, we treat the problem of learning averages out of a set of unitary matrices. We discuss a possible learning technique based on the differential geometrical properties of the Lie group of unitary matrices. We first recall some relevant notions from differential geometry, mainly related to Lie group theory, and then we propose a scheme for learning averages. Some numerical experiments will illustrate the features of the learnt averages. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IJCNN.2009.5178714 | IJCNN |
Keywords | Field | DocType |
lie group theory,numerical experiment,learnt average,present paper,lie group,relevant notion,differential geometry,differential geometrical property,possible learning technique,unitary matrix,symmetric matrices,lie algebras,matrix decomposition,nonlinear optics,signal processing,holography,optical scattering,learning artificial intelligence,quantum computing,lie groups,manifolds,data mining,unitary matrices | Lie group,Algebra,Circular ensemble,Representation of a Lie group,Unitary matrix,Pure mathematics,Differential geometry,Adjoint representation,Lie algebra,Gell-Mann matrices,Mathematics | Conference |
ISSN | Citations | PageRank |
2161-4393 | 0 | 0.34 |
References | Authors | |
8 | 1 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simone Fiori | 1 | 494 | 52.86 |