Publications
Detailed Information
Structured laplacian support vector machines : 구조화된 커널을 이용한 Laplacian SVM 방법
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 전종우 | - |
| dc.contributor.author | 이상준 | - |
| dc.date.accessioned | 2009-12-14T08:32:10Z | - |
| dc.date.available | 2009-12-14T08:32:10Z | - |
| dc.date.copyright | 2008. | - |
| dc.date.issued | 2008 | - |
| dc.identifier.uri | http://dcollection.snu.ac.kr:80/jsp/common/DcLoOrgPer.jsp?sItemId=000000039348 | eng |
| dc.identifier.uri | https://hdl.handle.net/10371/20652 | - |
| dc.description | Thesis(doctors)--서울대학교 대학원 :통계학과,2008.2. | en |
| dc.format.extent | v, 68 leaves | en |
| dc.language.iso | en | - |
| dc.publisher | 서울대학교 대학원 | en |
| dc.subject | SVM | en |
| dc.subject | support vector machine | en |
| dc.subject | 준지도분류방법 | en |
| dc.subject | semi-supervised learning | en |
| dc.subject | 변수선택 | en |
| dc.subject | manifold approach | en |
| dc.subject | functional analysis of variance decomposition | en |
| dc.subject | variable selection | en |
| dc.title | Structured laplacian support vector machines | en |
| dc.title.alternative | 구조화된 커널을 이용한 Laplacian SVM 방법 | en |
| dc.type | Thesis | - |
| dc.contributor.department | 통계학과 | - |
| dc.description.degree | Doctor | en |
- Appears in Collections:
- Files in This Item:
- There are no files associated with this item.
Item View & Download Count
Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.