메뉴 건너뛰기




Volumn 1, Issue , 2010, Pages 539-544

Non-metric locality-sensitive hashing

Author keywords

[No Author keywords available]

Indexed keywords

BINARY BITS; COLLISION PROBABILITY; EMPIRICAL EVALUATIONS; FEATURE SPACE; HUMAN PERCEPTION; LOCALITY SENSITIVE HASHING; NON-METRIC; REPRODUCING KERNEL;

EID: 77958602311     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (46)

References (21)
  • 1
    • 37549058056 scopus 로고    scopus 로고
    • Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions
    • Andoni, A., and Indyk, P. 2008. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. Commun. ACM 51(1): 117-122.
    • (2008) Commun. ACM , vol.51 , Issue.1 , pp. 117-122
    • Andoni, A.1    Indyk, P.2
  • 2
    • 0002281365 scopus 로고
    • Parametric correspondence and chamfer matching: Two new techniques for image matching
    • Barrow, H. G.; Tenenbaum, J. M.; Bolles, R. C; and Wolf, H. C. 1977. Parametric correspondence and chamfer matching: Two new techniques for image matching. In IJCAI, 659-663.
    • (1977) IJCAI , pp. 659-663
    • Barrow, H.G.1    Tenenbaum, J.M.2    Bolles, R.C.3    Wolf, H.C.4
  • 3
    • 0016557674 scopus 로고
    • Multidimensional binary search trees used for associative searching
    • Bentley, J. 1975. Multidimensional binary search trees used for associative searching. Commun. ACM 18(9):509-517.
    • (1975) Commun. ACM , vol.18 , Issue.9 , pp. 509-517
    • Bentley, J.1
  • 5
    • 49949144765 scopus 로고
    • The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming
    • Bregman, L. M. 1967. The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming. USSR Computational Mathematics and Mathematical Physics 7:200-217.
    • (1967) USSR Computational Mathematics and Mathematical Physics , vol.7 , pp. 200-217
    • Bregman, L.M.1
  • 7
    • 56449104479 scopus 로고    scopus 로고
    • Fast nearest neighbor retrieval for bregman divergences
    • Cayton, L. 2008. Fast nearest neighbor retrieval for bregman divergences. In ICML, 112-119.
    • (2008) ICML , pp. 112-119
    • Cayton, L.1
  • 8
    • 0036040277 scopus 로고    scopus 로고
    • Similarity estimation techniques from rounding algorithms
    • Charikar, M. 2002. Similarity estimation techniques from rounding algorithms. In STOC, 380-388.
    • (2002) STOC , pp. 380-388
    • Charikar, M.1
  • 10
    • 0031644241 scopus 로고    scopus 로고
    • Approximate nearest neighbors: Towards removing the curse of dimensionality
    • Indyk, P., and Motwani, R. 1998. Approximate nearest neighbors: towards removing the curse of dimensionality. In STOC.
    • (1998) STOC
    • Indyk, P.1    Motwani, R.2
  • 11
    • 0034204827 scopus 로고    scopus 로고
    • Classification with nonmetric distances: Image retrieval and class representation
    • Jacobs, D.; Weinshall, D.; and Gdalyahu, Y. 2000. Classification with nonmetric distances: Image retrieval and class representation. IEEE Trans. Pattern Anal. Mack Intell. 22(6):583-600.
    • (2000) IEEE Trans. Pattern Anal. Mack Intell. , vol.22 , Issue.6 , pp. 583-600
    • Jacobs, D.1    Weinshall, D.2    Gdalyahu, Y.3
  • 12
    • 77953184849 scopus 로고    scopus 로고
    • Kernelized locality-sensitive hashing for scalable image search
    • Kulis, B., and Grauman, K. 2009. Kernelized locality-sensitive hashing for scalable image search. In ICCV.
    • (2009) ICCV
    • Kulis, B.1    Grauman, K.2
  • 14
    • 77958581102 scopus 로고    scopus 로고
    • Inducing metric violations in human similarity judgements
    • Laub, J.; Macke, J.; Müller, K.-R.; and Wichmann, F. A. 2006. Inducing metric violations in human similarity judgements. In NIPS, 777-784.
    • (2006) NIPS , pp. 777-784
    • Laub, J.1    MacKe, J.2    Müller, K.-R.3    Wichmann, F.A.4
  • 17
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • Schölkopf, B.; Smola, A. J.; and Müller, K.-R. 1998. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation 10(5): 1299-1319.
    • (1998) Neural Computation , vol.10 , Issue.5 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.J.2    Müller, K.-R.3
  • 18
    • 58149411184 scopus 로고
    • Features of similarity
    • Tversky, A. 1977. Features of similarity. Psychological Review 84:327-352.
    • (1977) Psychological Review , vol.84 , pp. 327-352
    • Tversky, A.1
  • 19
    • 0027188633 scopus 로고
    • Data structures and algorithms for nearest neighbor search in general metric spaces
    • Yianilos, P. N. 1993. Data structures and algorithms for nearest neighbor search in general metric spaces. In SODA.
    • (1993) SODA
    • Yianilos, P.N.1
  • 20
    • 0002361037 scopus 로고
    • Discussion of a set of points in terms of their mutual distances
    • Young, G., and Householder, A. 1938. Discussion of a set of points in terms of their mutual distances. Psychometrika 3(1): 19-22.
    • (1938) Psychometrika , vol.3 , Issue.1 , pp. 19-22
    • Young, G.1    Householder, A.2
  • 21
    • 77956960464 scopus 로고    scopus 로고
    • Similarity search on bregman divergence: Towards non-metric indexing
    • Zhang, Z.; Ooi, B. C; Parthasarathy, S.; and Tung, A. K. H. 2009. Similarity search on bregman divergence: Towards non-metric indexing. PVLDB 2(1): 13-24.
    • (2009) PVLDB , vol.2 , Issue.1 , pp. 13-24
    • Zhang, Z.1    Ooi, B.C.2    Parthasarathy, S.3    Tung, A.K.H.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.