메뉴 건너뛰기




Volumn 4, Issue , 2006, Pages 202-205

Locally multidimensional scaling for nonlinear dimensionality reduction

Author keywords

Dimensionality reduction; Locally linear embedding; Manifold learning; Multidimensional scaling

Indexed keywords

DATA STRUCTURES; MATHEMATICAL MODELS; OPTIMIZATION; PROBLEM SOLVING;

EID: 34147116663     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2006.774     Document Type: Conference Paper
Times cited : (10)

References (8)
  • 1
    • 0041654220 scopus 로고
    • Multidimensional scaling by optimizing goodness-of-fit to a nonmetric hypothesis
    • J. Kruskal. Multidimensional scaling by optimizing goodness-of-fit to a nonmetric hypothesis. Psychometrika, 29:1-27, 1964.
    • (1964) Psychometrika , vol.29 , pp. 1-27
    • Kruskal, J.1
  • 2
    • 0018434328 scopus 로고
    • A fast converging algorithm for nonlinear mapping of high-dimensional data onto a plane
    • Feb
    • H. Niemann and J. Weiss. A fast converging algorithm for nonlinear mapping of high-dimensional data onto a plane. IEEE Trans. Computers, C-28(2): 142-147, Feb. 1979.
    • (1979) IEEE Trans. Computers , vol.C-28 , Issue.2 , pp. 142-147
    • Niemann, H.1    Weiss, J.2
  • 3
    • 0034704222 scopus 로고    scopus 로고
    • Nonlineaar dimensionality reduction by locally linear embedding
    • Dec
    • S. T. Roweis and L. K. Saul. Nonlineaar dimensionality reduction by locally linear embedding. Science, 290:2323-2326, Dec. 2000.
    • (2000) Science , vol.290 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 4
    • 84887006810 scopus 로고
    • A nonlinear mapping for data structure analysis
    • May
    • J. W. Sammon, Jr. A nonlinear mapping for data structure analysis. IEEE Trans. Computers, C-18(5):401-409, May 1969.
    • (1969) IEEE Trans. Computers , vol.C-18 , Issue.5 , pp. 401-409
    • Sammon Jr., J.W.1
  • 5
    • 2342517502 scopus 로고    scopus 로고
    • Think globally, fit locally: Unsupervised learning of low dimensional manifolds
    • June
    • L. K. Saul and S. T. Roweis. Think globally, fit locally: Unsupervised learning of low dimensional manifolds. J. Machine Learning Research, 4:119-155, June 2003.
    • (2003) J. Machine Learning Research , vol.4 , pp. 119-155
    • Saul, L.K.1    Roweis, S.T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.