| dc.contributor | Universidad Nacional de Asunción - Facultad Politécnica | |
| dc.creator | Mendoza Granada, Fabricio Augusto | |
| dc.creator | Cáceres Mercado, Sergio | |
| dc.creator | Villagra, Marcos | |
| dc.date | 2022-04-27T18:57:55Z | |
| dc.date | 2022-04-27T18:57:55Z | |
| dc.date | 2018 | |
| dc.date.accessioned | 2023-09-25T13:31:13Z | |
| dc.date.available | 2023-09-25T13:31:13Z | |
| dc.identifier | http://hdl.handle.net/20.500.14066/3728 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/8807238 | |
| dc.description | An important technique in data analysis is principal component analysis or PCA. Given a covariance matrix S, in PCA we need to compute the eigenvector associated to a greatest eigenvalue of S in order to determine the direction of the so-called principal components. | |
| dc.description | CONACYT – Consejo Nacional de Ciencia y Tecnología | |
| dc.description | PROCIENCIA | |
| dc.language | eng | |
| dc.relation | PINV15-208 | |
| dc.rights | open access | |
| dc.subject | 4 Transporte, telecomunicaciones y otras infraestructuras | |
| dc.subject | MATEMATICAS | |
| dc.subject | COMPUTACION | |
| dc.title | Deterministic graph spectral sparsification | |
| dc.type | conference paper | |
