Learning binary codes with Bagging PCA

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8725 LNAI, Issue PART 2, 2014, Pages 177-192

  Leng, Cong ^a   Cheng, Jian ^a   Yuan, Ting ^a   Bai, Xiao ^b   Lu, Hanqing ^a  

^a INSTITUTE OF AUTOMATION   (China)

^b BEIHANG UNIVERSITY   (China)

Author keywords

bagging; binary codes; Bootstrap; Hamming ranking; PCA; random

Indexed keywords

EID: 84907044667     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-662-44851-9_12     Document Type: Conference Paper

References (29)

1. Andoni, A., Indyk, P.: Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. In: Proceeding of the Annual IEEE Symposium on Foundations of Computer Science (2006)
2. Breiman, L.: Bagging predictors. Machine Learning 24(2), 123-140 (1996)
3. Broder, A.Z., Charikar, M., Frieze, A.M., Mitzenmacher, M.: Min-wise independent permutations. In: Proceedings of the Annual ACM Symposium on Theory of Computing (1998)
4. Charikar, M.: Similarity estimation techniques from rounding algorithm. In: ACM Symposium on Theory of Computing, pp. 380-388 (2002)
5. Dean, T., Ruzon, M.A., Segal, M., Shlens, J., Vijayanarasimhan, S., Yagnik, J.: Fast, accurate detection of 100,000 object classes on a single machine. In: IEEE Conference on Computer Vision and Pattern Recognition (2013)
6. Efron, B., Tibshirani, R.: An introduction to the bootstrap, vol. 57. CRC press (1993)
7. Gong, Y., Lazebnik, S.: Iterative quantization: A procrustean approach to learning binary codes. In: IEEE Conference on Computer Vision and Pattern Recognition (2011)
8. He, J., Liu, W., Chang, S.F.: Scalable similarity search with optimized kernel hashing. In: Proceedings of the ACM SIGKDD Conference (2010)
9. He, K., Wen, F., Sun, J.: K-means hashing: an affinity-preserving quantization method for learning binary compact codes. In: IEEE Conference on Computer Vision and Pattern Recognition (2013)
10. He, X., Niyogi, P.: Locality preserving projections. In: Advances in Neural Information Processing Systems (2003)
11. Heo, J., Lee, Y., He, J., Chang, S., Yoon, S.: Spherical hashing. In: IEEE Conference on Computer Vision and Pattern Recognition (2012)
12. Hoeffding, W.: Probability inequalities for sums of bounded random variables. Journal of the American Statistical Association 58(301), 13-30 (1963)
13. Indyk, P., Motwani, R.: Approximate nearest neighbors: towards removing the curse of dimensionality. In: Proceedings of ACM Symposium on Theory of Computing (1998)
14. Jégou, H., Douze, M., Schmid, C., Pérez, P.: Aggregating local descriptors into a compact image representation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3304-3311. IEEE (2010)
15. Kong, W., Li, W.: Isotropic hashing. In: Advances in Neural Information Processing Systems (2012)
16. Leng, C., Cheng, J., Lu, H.: Random subspace for binary codes learning in large scale image retrieval. In: Proceedings of ACM SIGIR Conference, SIGIR (2014)
17. Liu, W., Wang, J., Ji, R., Jiang, Y., Chang, S.: Supervised hashing with kernels. In: IEEE Conference on Computer Vision and Pattern Recognition (2012)
18. Liu, W., Wang, J., Kumar, S., Chang, S.: Hashing with graphs. In: Proceedings of the International Conference on Machine Learning (2011)
19. Oliva, A., Torralba, A.: Modeling the shape of the scene: A holistic representation of the spatial envelope. International Journal of Computer Vision 42(3), 145-175 (2001)
20. Shrivastava, A., Li, P.: Fast near neighbor search in high-dimensional binary data. In: Flach, P.A., De Bie, T., Cristianini, N. (eds.) ECML PKDD 2012, Part I. LNCS, vol. 7523, pp. 474-489. Springer, Heidelberg (2012)
21. Shrivastava, A., Li, P.: In defense of minhash over simhash. In: Proceedings of International Conference on Artificial Intelligence and Statistics (2014)
22. Skurichina, M., Duin, R.P.: Bagging, boosting and the random subspace method for linear classifiers. Pattern Analysis & Applications 5(2), 121-135 (2002)
23. Strecha, C., Bronstein, A.M., Bronstein, M.M., Fua, P.: Ldahash: Improved matching with smaller descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(1), 66-78 (2012)
24. Wang, J., Kumar, S., Chang, S.F.: Semi-supervised hashing for scalable image retrieval. In: IEEE Conference on Computer Vision and Pattern Recognition (2010)
25. Wang, J., Kumar, S., Chang, S.F.: Sequential projection learning for hashing with compact codes. In: Proceedings of International Conference on Machine Learning, pp. 1127-1134 (2010)
26. Weiss, Y., Torralba, A., Fergus, R.: Spectral hashing. In: Advances in Neural Information Processing Systems (2008)
27. Xu, B., Bu, J., Lin, Y., Chen, C., He, X., Cai, D.: Harmonious hashing. In: Proceedings of International Joint Conference on Artificial Intelligence (2013)
28. Yu, S.X., Shi, J.: Multiclass spectral clustering. In: Proceedings of the International Conference on Computer Vision (2003)
29. Zhang, D., Wang, J., Cai, D., Lu, J.: Self-taught hashing for fast similarity search. In: Proceedings of International ACM SIGIR Conference (2010)