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References Strecha.C.:Bronstein,A.A.:Bronstein.M.M.:and Fua.P Andoni,A.,and Indyk,P.2006. Near-optimal hashing 2012.Ldahash:Improved matching with smaller descriptors. algorithms for approximate nearest neighbor in high dimensions. IEEE Transactions on Pattern Analysis and Machine Intelligence In Proceedings of the Annual Symposium on Foundations of 341):66-78. Computer Science. Wang,J.;Kumar,O.;and Chang,S.-F.2010a.Semi-supervised Chua,T.-S.;Tang,J.;Hong.R.;Li,H.;Luo,Z.;and Zheng, hashing for scalable image retrieval.In Proceedings of the IEEE Y.2009.NUS-WIDE:A real-world web image database from Conference on Computer Vision and Pattern Recognition national university of singapore.In Proceedings of the ACM Wang,J.;Kumar,S.;and Chang,S.-F.2010b.Sequential projection International Conference on Image and Video Retrieval. learning for hashing with compact codes.In Proceedings of the Ge,T.;He,K.;and Sun,J.2014.Graph cuts for supervised binary International Conference on Machine Learning coding.In Proceedings of the European Conference on Computer Wang,Q.;Zhang,D.;and Si,L.2013.Semantic hashing using Vision. tags and topic modeling.In Proceedings of the International ACM Gong,Y.,and Lazebnik,S.2011.Iterative quantization:A SIGIR conference on research and development in Information procrustean approach to learning binary codes.In Proceedings of Retrieval. the IEEE Conference on Computer Vision and Pattern Recognition. Weiss,Y.:Torralba,A.;and Fergus,R.2008.Spectral hashing Indyk,P.,and Motwani,R.1998.Approximate nearest neighbors: In Proceedings of the Annual Conference on Neural Information Towards removing the curse of dimensionality.In Proceedings of Processing Systems. the Annual ACM Symposium on Theory of Computing. Xia.R.:Pan.Y.:Lai,H.:Liu.C.:and Yan.S.2014.Supervised Jiang,Q.-Y.,and Li,W.-J.2015.Scalable graph hashing with hashing for image retrieval via image representation learing.In feature transformation.In Proceedings of the International Joint Proceedings of the AAAl Conference on Artificial Intelligence. Conference on Artificial Intelligence. Xu,B.;Bu,J.;Lin,Y.;Chen,C.;He,X.;and Cai,D.2013. Jin,Z.;Hu,Y.;Lin,Y.;Zhang,D.:Lin,S.;Cai,D.;and Li,X. Harmonious hashing.In Proceedings of the International Joint 2013.Complementary projection hashing.In Proceedings of the Conference on Artificial Intelligence. IEEE International Conference on Computer Vision. Yang,R.2013.New Results on Some Quadratic Programming Kong,W.,and Li,W.-J.2012.Isotropic hashing.In Proceedings of Problems.Phd thesis,University of Illinois at Urbana-Champaign. the Annual Conference on Neural Information Processing Systems. Yu,Z.;Wu,F.;Yang,Y.;Tian,Q.;Luo,J.;and Zhuang,Y. Krizhevsky,A.2009.Learning multiple layers of features from 2014.Discriminative coupled dictionary hashing for fast cross- tiny images.Master's thesis,University of Toronto. media retrieval.In Proceedings of the International ACM Kulis,B.,and Grauman,K.2009.Kernelized locality-sensitive SIGIR Conference on Research and Development in Information hashing for scalable image search.In Proceedings of the IEEE Retrieval. International Conference on Computer Vision. Zhang,D.,and Li,W.-J.2014.Large-scale supervised multimodal Leng.C.;Cheng.J.;Wu,J.;Zhang,X.;and Lu,H.2014. hashing with semantic correlation maximization.In Proceedings Supervised hashing with soft constraints.In Proceedings of the of the AAAl Conference on Artificial Intelligence. ACM International Conference on Conference on Information and Zhang.D.;Wang.J.;Cai,D.;and Lu,J.2010.Self-taught hashing Knowledge Management. for fast similarity search.In Proceedings of the International ACM Lin,G.;Shen,C.;Suter,D.;and Hengel,A.v.d.2013a.A general SIGIR Conference on Research and Development in Information Retrieval. two-step approach to learning-based hashing.In Proceedings of the IEEE International Conference on Computer Vision. Zhang.Q.;Wu,Y.;Ding.Z.;and Huang.X.2012.Learning Lin,Y.;Jin,R.:Cai,D.:Yan,S.;and Li,X.2013b.Compressed hash codes for efficient content reuse detection.In Proceedings hashing.In Proceedings of the IEEE Conference on Computer of the International ACM SIGIR Conference on Research and Vision and Pattern Recognition. Development in Information Retrieval. 2014 Lin,G.;Shen,C.;Shi,Q.;van den Hengel,A.;and Suter,D.2014. Zhang.P:Zhang,W.;Li,W.-J.;and Guo,M. Fast supervised hashing with decision trees for high-dimensional Supervised hashing with latent factor models.In Proceedings data.In Proceedings of the IEEE Conference on Computer Vision of the International ACM SIGIR Conference on Research and and Pattern Recognition. Development in Information Retrieval. Liu,W.;Wang,J.;Ji,R.;Jiang.Y.-G.;and Chang,S.-F.2012. Zhang,D.;Wang,F;and Si,L.2011.Composite hashing with Supervised hashing with kernels.In Proceedings of the IEEE multiple information sources.In Proceedings of the International Conference on Computer Vision and Pattern Recognition ACM SIGIR Conference on Research and Development in Information Retrieval. Liu,W.;Mu,C.;Kumar,S.;and Chang.S.2014.Discrete graph hashing.In Proceedings of the Annual Conference on Neural Zhen,Y.,and Yeung.D.-Y.2012.A probabilistic model for Information Processing Systems. multimodal hash function learning.In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Norouzi,M.,and Fleet,D.J.2011.Minimal loss hashing Data Mining. for compact binary codes.In Proceedings of the International Conference on Machine Learning. Zhou,J.;Ding,G.;and Guo,Y.2014.Latent semantic sparse hashing for cross-modal similarity search.In Proceedings Rastegari,M.:Choi,J.:Fakhraei.S.:Hal,D.:and Davis,L.S.2013. of the International ACM SIGIR Conference on Research and Predictable dual-view hashing.In Proceedings of the International Development in Information Retrieval. Conference on Machine Learning. Zhu,X.;Huang.Z.:Shen,H.T.;and Zhao,X.2013.Linear cross- Shen,F.;Shen,C.;Liu,W.;and Shen,H.T.2015.Supervised modal hashing for efficient multimedia search.In Proceedings of discrete hashing.In Proceedings of the IEEE Conference on the ACM International Conference on Multimedia. Computer Vision and Pattern Recognition.References Andoni, A., and Indyk, P. 2006. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. In Proceedings of the Annual Symposium on Foundations of Computer Science. Chua, T.-S.; Tang, J.; Hong, R.; Li, H.; Luo, Z.; and Zheng, Y. 2009. NUS-WIDE: A real-world web image database from national university of singapore. In Proceedings of the ACM International Conference on Image and Video Retrieval. Ge, T.; He, K.; and Sun, J. 2014. Graph cuts for supervised binary coding. In Proceedings of the European Conference on Computer Vision. Gong, Y., and Lazebnik, S. 2011. Iterative quantization: A procrustean approach to learning binary codes. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Indyk, P., and Motwani, R. 1998. Approximate nearest neighbors: Towards removing the curse of dimensionality. In Proceedings of the Annual ACM Symposium on Theory of Computing. Jiang, Q.-Y., and Li, W.-J. 2015. Scalable graph hashing with feature transformation. In Proceedings of the International Joint Conference on Artificial Intelligence. Jin, Z.; Hu, Y.; Lin, Y.; Zhang, D.; Lin, S.; Cai, D.; and Li, X. 2013. Complementary projection hashing. In Proceedings of the IEEE International Conference on Computer Vision. Kong, W., and Li, W.-J. 2012. Isotropic hashing. In Proceedings of the Annual Conference on Neural Information Processing Systems. Krizhevsky, A. 2009. Learning multiple layers of features from tiny images. Master’s thesis, University of Toronto. Kulis, B., and Grauman, K. 2009. Kernelized locality-sensitive hashing for scalable image search. In Proceedings of the IEEE International Conference on Computer Vision. Leng, C.; Cheng, J.; Wu, J.; Zhang, X.; and Lu, H. 2014. Supervised hashing with soft constraints. In Proceedings of the ACM International Conference on Conference on Information and Knowledge Management. Lin, G.; Shen, C.; Suter, D.; and Hengel, A. v. d. 2013a. A general two-step approach to learning-based hashing. In Proceedings of the IEEE International Conference on Computer Vision. Lin, Y.; Jin, R.; Cai, D.; Yan, S.; and Li, X. 2013b. Compressed hashing. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Lin, G.; Shen, C.; Shi, Q.; van den Hengel, A.; and Suter, D. 2014. Fast supervised hashing with decision trees for high-dimensional data. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Liu, W.; Wang, J.; Ji, R.; Jiang, Y.-G.; and Chang, S.-F. 2012. Supervised hashing with kernels. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Liu, W.; Mu, C.; Kumar, S.; and Chang, S. 2014. Discrete graph hashing. In Proceedings of the Annual Conference on Neural Information Processing Systems. Norouzi, M., and Fleet, D. J. 2011. Minimal loss hashing for compact binary codes. In Proceedings of the International Conference on Machine Learning. Rastegari, M.; Choi, J.; Fakhraei, S.; Hal, D.; and Davis, L. S. 2013. Predictable dual-view hashing. In Proceedings of the International Conference on Machine Learning. Shen, F.; Shen, C.; Liu, W.; and Shen, H. T. 2015. Supervised discrete hashing. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Strecha, C.; Bronstein, A. A.; Bronstein, M. M.; and Fua, P. 2012. Ldahash: Improved matching with smaller descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(1):66–78. Wang, J.; Kumar, O.; and Chang, S.-F. 2010a. Semi-supervised hashing for scalable image retrieval. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Wang, J.; Kumar, S.; and Chang, S.-F. 2010b. Sequential projection learning for hashing with compact codes. In Proceedings of the International Conference on Machine Learning. Wang, Q.; Zhang, D.; and Si, L. 2013. Semantic hashing using tags and topic modeling. In Proceedings of the International ACM SIGIR conference on research and development in Information Retrieval. Weiss, Y.; Torralba, A.; and Fergus, R. 2008. Spectral hashing. In Proceedings of the Annual Conference on Neural Information Processing Systems. Xia, R.; Pan, Y.; Lai, H.; Liu, C.; and Yan, S. 2014. Supervised hashing for image retrieval via image representation learning. In Proceedings of the AAAI Conference on Artificial Intelligence. Xu, B.; Bu, J.; Lin, Y.; Chen, C.; He, X.; and Cai, D. 2013. Harmonious hashing. In Proceedings of the International Joint Conference on Artificial Intelligence. Yang, R. 2013. New Results on Some Quadratic Programming Problems. Phd thesis, University of Illinois at Urbana-Champaign. Yu, Z.; Wu, F.; Yang, Y.; Tian, Q.; Luo, J.; and Zhuang, Y. 2014. Discriminative coupled dictionary hashing for fast cross￾media retrieval. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval. Zhang, D., and Li, W.-J. 2014. Large-scale supervised multimodal hashing with semantic correlation maximization. In Proceedings of the AAAI Conference on Artificial Intelligence. Zhang, D.; Wang, J.; Cai, D.; and Lu, J. 2010. Self-taught hashing for fast similarity search. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval. Zhang, Q.; Wu, Y.; Ding, Z.; and Huang, X. 2012. Learning hash codes for efficient content reuse detection. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval. Zhang, P.; Zhang, W.; Li, W.-J.; and Guo, M. 2014. Supervised hashing with latent factor models. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval. Zhang, D.; Wang, F.; and Si, L. 2011. Composite hashing with multiple information sources. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval. Zhen, Y., and Yeung, D.-Y. 2012. A probabilistic model for multimodal hash function learning. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Zhou, J.; Ding, G.; and Guo, Y. 2014. Latent semantic sparse hashing for cross-modal similarity search. In Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval. Zhu, X.; Huang, Z.; Shen, H. T.; and Zhao, X. 2013. Linear cross￾modal hashing for efficient multimedia search. In Proceedings of the ACM International Conference on Multimedia
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