메뉴 건너뛰기




Volumn 10, Issue 4, 2016, Pages

Heterogeneous translated hashing: A scalable solution towards multi-modal similarity search

Author keywords

Hash function learning; Heterogeneous translated hashing; Scalability; Similarity search

Indexed keywords

OPTIMIZATION; SCALABILITY;

EID: 84995581954     PISSN: 15564681     EISSN: 1556472X     Source Type: Journal    
DOI: 10.1145/2744204     Document Type: Article
Times cited : (15)

References (45)
  • 1
    • 38749118638 scopus 로고    scopus 로고
    • Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions
    • ACM
    • A. Andoni and P. Indyk. 2006. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. In FOCS. ACM, 459-468. DOI:http://dx.doi.org/10.1109/FOCS.2006.49
    • (2006) FOCS , pp. 459-468
    • Andoni, A.1    Indyk, P.2
  • 2
    • 0016557674 scopus 로고
    • Multidimensional binary search trees used for associative searching
    • Jon Louis Bentley. 1975. Multidimensional binary search trees used for associative searching. Commun. ACM 18, 9 (1975), 509-517.
    • (1975) Commun. ACM , vol.18 , Issue.9 , pp. 509-517
    • Louis Bentley, J.1
  • 4
    • 0141607824 scopus 로고    scopus 로고
    • Latent Dirichlet allocation
    • 2003
    • David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent Dirichlet allocation. J. Mach. Learn. Res. 3 (2003), 993-1022.
    • (2003) J. Mach. Learn. Res , vol.3 , pp. 993-1022
    • Blei, D.M.1    Ng, A.Y.2    Jordan, M.I.3
  • 5
    • 77955989956 scopus 로고    scopus 로고
    • Data fusion through cross-modality metric learning using similarity-sensitive hashing
    • IEEE Computer Society
    • M. M. Bronstein, A. M. Bronstein, F. Michel, and N. Paragios. 2010. Data fusion through cross-modality metric learning using similarity-sensitive hashing. In CVPR. IEEE Computer Society, 3594-3601. DOI:http://dx.doi.org/10.1109/CVPR.2010.5539928
    • (2010) CVPR , pp. 3594-3601
    • Bronstein, M.M.1    Bronstein, A.M.2    Michel, F.3    Paragios, N.4
  • 6
    • 72249085330 scopus 로고    scopus 로고
    • NUS-WIDE: A real-world web image database from national university of Singapore
    • ACM
    • Tat-Seng Chua, Jinhui Tang, Richang Hong, Haojie Li, Zhiping Luo, and Yan-Tao. Zheng. 2009. NUS-WIDE: A real-world web image database from national university of Singapore. In VLDB. ACM, 48:1-48:9.
    • (2009) VLDB , pp. 481-489
    • Chua, T.1    Tang, J.2    Hong, R.3    Li, H.4    Luo, Z.5    Zheng, Y.6
  • 7
    • 4544259509 scopus 로고    scopus 로고
    • Locality-sensitive hashing scheme based on P-stable distributions
    • ACM
    • Mayur Datar,Nicole Immorlica, Piotr Indyk, and Vahab S. Mirrokni. 2004. Locality-sensitive hashing scheme based on P-stable distributions. In SCG. ACM, 253-262. DOI:http://dx.doi.org/10.1145/997817.997857
    • (2004) SCG , pp. 253-262
    • Datarnicole, I.P.1    Indyk, M.2    Mirrokni, V.S.3
  • 9
    • 0001944742 scopus 로고    scopus 로고
    • Similarity search in high dimensions via hashing
    • Morgan Kaufmann Publishers Inc
    • Aristides Gionis, Piotr Indyk, and Rajeev Motwani. 1999. Similarity search in high dimensions via hashing. In VLDB. Morgan Kaufmann Publishers Inc., 518-529. http://dl.acm.org/citation.cfm?id=645925.671516
    • (1999) VLDB , pp. 518-529
    • Gionis, A.1    Indyk, P.2    Motwani, R.3
  • 10
    • 80052874105 scopus 로고    scopus 로고
    • Iterative quantization: A procrustean approach to learning binary codes
    • IEEE Computer Society
    • Yunchao Gong and S. Lazebnik. 2011. Iterative quantization: A procrustean approach to learning binary codes. In CVPR. IEEE Computer Society, 817-824. DOI:http://dx.doi.org/10.1109/CVPR.2011.5995432
    • (2011) CVPR , pp. 817-824
    • Gong, Y.1    Lazebnik, S.2
  • 11
    • 29144534131 scopus 로고    scopus 로고
    • Convergence theorems for generalized alternating minimization procedures
    • Asela Gunawardana andWilliam Byrne. 2005. Convergence theorems for generalized alternating minimization procedures. J. Mach. Learn. Res. 6 (2005), 2049-2073.
    • (2005) J. Mach. Learn. Res , vol.6 , pp. 2049-2073
    • Gunawardana, A.1    Byrne, W.2
  • 12
    • 70449621223 scopus 로고    scopus 로고
    • The miR flickr retrieval evaluation
    • ACM
    • Mark J. Huiskes and Michael S. Lew. 2008. The MIR Flickr retrieval evaluation. In MIR. ACM, 39-43. DOI:http://dx.doi.org/10.1145/1460096.1460104
    • (2008) MIR , pp. 39-43
    • Huiskes, M.J.1    Lew, M.S.2
  • 13
    • 77953184849 scopus 로고    scopus 로고
    • Kernelized locality-sensitive hashing for scalable image search
    • IEEE Computer Society
    • B. Kulis and K. Grauman. 2009. Kernelized locality-sensitive hashing for scalable image search. In ICCV. IEEE Computer Society, 2130-2137. DOI:http://dx.doi.org/10.1109/ICCV.2009.5459466
    • (2009) ICCV , pp. 2130-2137
    • Kulis, B.1    Grauman, K.2
  • 15
    • 84866034209 scopus 로고    scopus 로고
    • Learning hash functions for cross-view similarity search
    • AAAI Press
    • Shaishav Kumar and Raghavendra Udupa. 2011. Learning hash functions for cross-view similarity search. In IJCAI. AAAI Press, 1360-1365. DOI:http://dx.doi.org/10.5591/978-1-57735-516-8/IJCAI11-230
    • (2011) IJCAI , pp. 1360-1365
    • Kumar, S.1    Udupa, R.2
  • 16
    • 78149477774 scopus 로고    scopus 로고
    • Sriperumbudur On the convergence of the concave-convex procedure
    • Curran Associates, Inc
    • Gert R. Lanckriet and BharathK. Sriperumbudur. 2009. On the convergence of the concave-convex procedure. In Advances in Neural Information Processing Systems. Curran Associates, Inc., 1759-1767.
    • (2009) Advances in Neural Information Processing Systems , pp. 1759-1767
    • Lanckriet, G.R.1    Bharath, K.2
  • 17
    • 80053456121 scopus 로고    scopus 로고
    • Hashing with graphs
    • ACM
    • Wei Liu, Jun Wang, Sanjiv Kumar, and Shih-Fu Chang. 2011. Hashing with graphs. In ICML. ACM, 1-8.
    • (2011) ICML , pp. 1-8
    • Liu, W.1    Wang, J.2    Kumar, S.3    Chang, S.4
  • 18
    • 0016923670 scopus 로고
    • Sufficient conditions for the convergence of monotonic mathematicalprogramming algorithms
    • R. R. Meyer. 1976. Sufficient conditions for the convergence of monotonic mathematicalprogramming algorithms. J. Comput. Syst. Sci. 12, 1 (1976), 108-121.
    • (1976) J. Comput. Syst. Sci , vol.12 , Issue.1 , pp. 108-121
    • Meyer, R.R.1
  • 19
    • 77955986970 scopus 로고    scopus 로고
    • Weakly-supervised hashing in kernel space
    • IEEE Computer Society
    • Yadong Mu, Jialie Shen, and Shuicheng Yan. 2010. Weakly-supervised hashing in kernel space. In CVPR. IEEE Computer Society, 3344-3351. DOI:http://dx.doi.org/10.1109/CVPR.2010.5540024
    • (2010) CVPR , pp. 3344-3351
    • Mu, Y.1    Shen, J.2    Yan, S.3
  • 20
    • 84999832326 scopus 로고    scopus 로고
    • Comparing apples to oranges: A scalable solution with heterogeneous hashing
    • ACM
    • Mingdong Ou, Peng Cui, Fei Wang, Jun Wang, Wenwu Zhu, and Shiqiang Yang. 2013. Comparing apples to oranges: A scalable solution with heterogeneous hashing. In KDD. ACM, 230-238. DOI:http://dx.doi.org/10.1145/2487575.2487668
    • (2013) KDD , pp. 230-238
    • Ou, M.1    Cui, P.2    Wang, F.3    Wang, J.4    Zhu, W.5    Yang, S.6
  • 21
    • 80053439603 scopus 로고    scopus 로고
    • Learning multi-view neighborhood preserving projections
    • ACM
    • N. Quadrianto and C. Lampert. 2011. Learning multi-view neighborhood preserving projections. In ICML.ACM, 425-432.
    • (2011) ICML , pp. 425-432
    • Quadrianto, N.1    Lampert, C.2
  • 22
    • 79954525255 scopus 로고    scopus 로고
    • Locality-sensitive binary codes from shift-invariant kernels
    • Curran Associates, Inc
    • Maxim Raginsky and Svetlana Lazebnik. 2009. Locality-sensitive binary codes from shift-invariant kernels. In NIPS. Curran Associates, Inc., 1509-1517.
    • (2009) NIPS , pp. 1509-1517
    • Raginsky, M.1    Lazebnik, S.2
  • 23
    • 67449128732 scopus 로고    scopus 로고
    • Semantic hashing
    • 2009
    • Ruslan Salakhutdinov and Geoffrey Hinton. 2009. Semantic hashing. Int. J. Approx. Reason. 50, 7 (2009), 969-978. DOI:http://dx.doi.org/10.1016/j.ijar.2008.11.006
    • (2009) Int. J. Approx. Reason , vol.50 , Issue.7 , pp. 969-978
    • Salakhutdinov, R.1    Hinton, G.2
  • 24
    • 0345414554 scopus 로고    scopus 로고
    • Fast pose estimation with parameter-sensitive hashing
    • IEEE Computer Society
    • G. Shakhnarovich, P. Viola, and T. Darrell. 2003. Fast pose estimation with parameter-sensitive hashing. In ICCV. IEEE Computer Society, 750-757. DOI:http://dx.doi.org/10.1109/ICCV.2003.1238424
    • (2003) ICCV , pp. 750-757
    • Shakhnarovich, G.1    Viola, P.2    Darrell, T.3
  • 25
    • 34547964973 scopus 로고    scopus 로고
    • Pegasos: Primal estimated sub-gradient solver for SVM
    • ACM
    • Shai Shalev-Shwartz, Yoram Singer, and Nathan Srebro. 2007. Pegasos: Primal estimated sub-gradient solver for SVM. In ICML. ACM, 807-814. DOI:http://dx.doi.org/10.1145/1273496.1273598
    • (2007) ICML , pp. 807-814
    • Shalev-Shwartz, S.1    Singer, Y.2    Srebro, N.3
  • 26
    • 79952748054 scopus 로고    scopus 로고
    • Pegasos: Primal estimated sub-gradient solver for SVM
    • 2011
    • Shai Shalev-Shwartz, Yoram Singer, Nathan Srebro, and Andrew Cotter. 2011. Pegasos: Primal estimated sub-gradient solver for SVM. Math. Program. 127, 1 (2011), 3-30. DOI:http://dx.doi.org/10.1007/s10107-010-0420-4
    • (2011) Math. Program , vol.127 , Issue.1 , pp. 3-30
    • Shalev-Shwartz, S.1    Singer, Y.2    Srebro, N.3    Cotter, A.4
  • 27
    • 84899744531 scopus 로고    scopus 로고
    • Multi-modal image retrieval for complex queries using small codes
    • ACM
    • Behjat Siddiquie, Brandyn White, Abhishek Sharma, and Larry S. Davis. 2014. Multi-modal image retrieval for complex queries using small codes. In ICMR. ACM, 321.
    • (2014) ICMR , pp. 321
    • Siddiquie, B.1    White, B.2    Sharma, A.3    Davis, L.S.4
  • 29
    • 84880548516 scopus 로고    scopus 로고
    • Inter-media hashing for largescale retrieval from heterogeneous data sources
    • ACM
    • Jingkuan Song, Yang Yang, Yi Yang, Zi Huang, and Heng Tao Shen. 2013. Inter-media hashing for largescale retrieval from heterogeneous data sources. In SIGMOD. ACM, 785-796. DOI:http://dx.doi.org/10.1145/2463676.2465274
    • (2013) SIGMOD , pp. 785-796
    • Song, J.1    Yang, Y.2    Yang, Y.3    Huang, Z.4    Tao Shen, H.5
  • 31
    • 0026256261 scopus 로고
    • Satisfying general proximity/similarity queries with metric trees
    • 1991
    • Jeffrey K. Uhlmann. 1991. Satisfying general proximity/similarity queries with metric trees. Inf. Process. Lett. 40, 4 (1991), 175-179.
    • (1991) Inf. Process. Lett , vol.40 , Issue.4 , pp. 175-179
    • Jeffrey, K.1    Uhlmann2
  • 32
    • 77955988108 scopus 로고    scopus 로고
    • Semi-supervised hashing for scalable image retrieval
    • IEEE Computer Society
    • Jun Wang, S. Kumar, and Shih-Fu Chang. 2010. Semi-supervised hashing for scalable image retrieval. In CVPR. IEEE Computer Society, 3424-3431. DOI:http://dx.doi.org/10.1109/CVPR.2010.5539994
    • (2010) CVPR , pp. 3424-3431
    • Wang, J.1    Kumar, S.2    Chang, S.3
  • 34
    • 0000681228 scopus 로고    scopus 로고
    • A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces
    • Morgan Kaufmann Publishers Inc
    • Roger Weber, Hans-Jörg Schek, and Stephen Blott. 1998. A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. In VLDB. Morgan Kaufmann Publishers Inc., 194-205. http://dl.acm.org/citation.cfm?id=645924.671192
    • (1998) VLDB , pp. 194-205
    • Weber, R.1    Schek, H.2    Blott, S.3
  • 36
    • 84858779327 scopus 로고    scopus 로고
    • Spectral hashing
    • Curran Associates, Inc
    • Yair Weiss, Antonio Torralba, and Rob Fergus. 2008. Spectral hashing. In NIPS. Curran Associates, Inc., 1753-1760.
    • (2008) NIPS , pp. 1753-1760
    • Weiss, Y.1    Torralba, A.2    Fergus, R.3
  • 40
    • 84896062612 scopus 로고    scopus 로고
    • Parametric local multimodal hashing for cross-view similarity search
    • AAAI Press
    • Deming Zhai, Hong Chang, Yi Zhen, Xianming Liu, Xilin Chen, and Wen Gao. 2013. Parametric local multimodal hashing for cross-view similarity search. In IJCAI. AAAI Press, 2754-2760. http://dl.acm.org/citation.cfm?id=2540128.2540525
    • (2013) IJCAI , pp. 2754-2760
    • Zhai, D.1    Chang, H.2    Zhen, Y.3    Liu, X.4    Chen, X.5    Gao, W.6
  • 41
    • 77956027394 scopus 로고    scopus 로고
    • Self-taught hashing for fast similarity search
    • ACM
    • Dell Zhang, Jun Wang, Deng Cai, and Jinsong Lu. 2010. Self-taught hashing for fast similarity search. In SIGIR. ACM, 18-25. DOI:http://dx.doi.org/10.1145/1835449.1835455
    • (2010) SIGIR , pp. 18-25
    • Zhang, D.1    Wang, J.2    Cai, D.3    Lu, J.4
  • 42
    • 84877748479 scopus 로고    scopus 로고
    • Co-regularized hashing for multimodal data
    • Curran Associates, Inc
    • Yi Zhen and Dit Yan Yeung. 2012a. Co-Regularized Hashing for Multimodal Data. In NIPS. Curran Associates, Inc., 1385-1393.
    • (2012) NIPS , pp. 1385-1393
    • Zhen, Y.1    Yan Yeung, D.2
  • 43
    • 84866037322 scopus 로고    scopus 로고
    • A probabilistic model for multimodal hash function learning
    • ACM
    • Yi Zhen and Dit Yan Yeung. 2012b. A probabilistic model for multimodal hash function learning. In KDD. ACM, 940-948. DOI:http://dx.doi.org/10.1145/2339530.2339678
    • (2012) KDD , pp. 940-948
    • Zhen, Y.1    Yan Yeung, D.2
  • 45
    • 84887418815 scopus 로고    scopus 로고
    • Linear cross-modal hashing for efficient multimedia search
    • ACM
    • Xiaofeng Zhu, Zi Huang, Heng Tao Shen, and Xin Zhao. 2013. Linear cross-modal hashing for efficient multimedia search. In MM. ACM, 143-152. DOI:http://dx.doi.org/10.1145/2502081.2502107
    • (2013) MM , pp. 143-152
    • Zhu, X.1    Huang, Z.2    Tao Shen, H.3    Zhao, X.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.