메뉴 건너뛰기




Volumn 68, Issue 2, 2007, Pages 171-200

Structured large margin machines: Sensitive to data distributions

Author keywords

Agglomerative hierarchical clustering; Homospace; Large margin learning; Second order cone programming (SOCP); Structured learning; Weighted Mahalanobis distance (WMD)

Indexed keywords

DATA REDUCTION; DATA STRUCTURES; SCALABILITY; SEQUENTIAL MACHINES;

EID: 34547446205     PISSN: 08856125     EISSN: 15730565     Source Type: Journal    
DOI: 10.1007/s10994-007-5015-9     Document Type: Article
Times cited : (69)

References (29)
  • 1
    • 0001614864 scopus 로고    scopus 로고
    • The MOSEK interior point optimizer for linear programming: An implementation of the homogeneous algorithm
    • Kluwer Academic Dordrecht
    • Andersen, E. D., & Andersen, A. D. (2001). The MOSEK interior point optimizer for linear programming: An implementation of the homogeneous algorithm. In High performance optimization (pp. 197-232). Dordrecht: Kluwer Academic.
    • (2001) High Performance Optimization , pp. 197-232
    • Andersen, E.D.1    Andersen, A.D.2
  • 2
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • Burges, C. (1998). A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2, 121-167.
    • (1998) Data Mining and Knowledge Discovery , vol.2 , pp. 121-167
    • Burges, C.1
  • 6
    • 0024686546 scopus 로고
    • Comparison of hierarchic agglomerative clustering methods of document retrieval
    • 3
    • El-Hamdouchi, A., & Willett, P. (1989). Comparison of hierarchic agglomerative clustering methods of document retrieval. The Computer Journal, 32(3), 220-227.
    • (1989) The Computer Journal , vol.32 , pp. 220-227
    • El-Hamdouchi, A.1    Willett, P.2
  • 8
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxonomic problems
    • Fisher, R. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7, 179-188.
    • (1936) Annals of Eugenics , vol.7 , pp. 179-188
    • Fisher, R.1
  • 9
    • 0036565280 scopus 로고    scopus 로고
    • Mercer kernel-based clustering in feature space
    • 3
    • Girolami, M. (2002). Mercer kernel-based clustering in feature space. IEEE Transactions on Neural Networks, 13(3), 780-784.
    • (2002) IEEE Transactions on Neural Networks , vol.13 , pp. 780-784
    • Girolami, M.1
  • 11
    • 0036505670 scopus 로고    scopus 로고
    • A comparison of methods for multiclass support vector machines
    • 2
    • Hsu, C. W., & Lin, C. J. (2002). A comparison of methods for multiclass support vector machines. IEEE Transactions on Neural Networks, 13(2), 415-425.
    • (2002) IEEE Transactions on Neural Networks , vol.13 , pp. 415-425
    • Hsu, C.W.1    Lin, C.J.2
  • 23
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • Schölkopf, B., Smola, A., & Müller, K.-R. (1998). Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10, 1299-1319.
    • (1998) Neural Computation , vol.10 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.-R.3
  • 25
    • 0033296299 scopus 로고    scopus 로고
    • Using Sedumi 1.02, a Matlab toolbox for optimization over symmetric cones
    • Sturm, J. (1999). Using Sedumi 1.02, a Matlab toolbox for optimization over symmetric cones. Optimization Methods and Software, 11, 625-653.
    • (1999) Optimization Methods and Software , vol.11 , pp. 625-653
    • Sturm, J.1
  • 29
    • 84944178665 scopus 로고
    • Hierarchical grouping to optimize an objective function
    • Ward, J. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58, 236-244.
    • (1963) Journal of the American Statistical Association , vol.58 , pp. 236-244
    • Ward, J.H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.