Active learning for sparse bayesian multilabel classification

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2014, Pages 472-481

  Vasisht, Deepak ^a   Damianou, Andreas ^b   Varma, Manik ^c   Kapoor, Ashish ^c  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b UNIVERSITY OF SHEFFIELD   (United Kingdom)

^c MICROSOFT RESEARCH   (United States)

Author keywords

active learning; multi label learning; mutual information

Indexed keywords

EID: 84907033525     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2623330.2623759     Document Type: Conference Paper

References (34)

1. Mulan Multilabel Datasets. http://mulan.sourceforge.net/datasets.html.
2. R. Agrawal, A. Gupta, Y. Prabhu, and M. Varma. Multi-label learning with millions of labels: Recommending advertiser bid phrases for web pages. In WWW, 2013.
3. K. Balasubramanian and G. Lebanon. The Landmark Selection Method for Multiple Output Prediction. In ICML, 2012.
4. A. Bergamo, L. Torresani, and A. W. Fitzgibbon. PiCoDes: Learning a Compact Code for Novel-Category Recognition. In NIPS, 2011.
5. W. Bi and J. T.-Y. Kwok. Efficient Multi-label Classification with Many Labels. In ICML, pages 405-413, 2013.
6. C. M. Bishop and M. E. Tipping. Variational Relevance Vector Machines. In UAI, 2000.
7. W. Caselton and J. Zidek. Optimal monitoring network designs . Statistics and Probability Letters, 1984.
8. Y.-N. Chen and H.-T. Lin. Feature-aware Label Space Dimension Reduction for Multi-label Classification. In NIPS, pages 1538-1546, 2012.
9. W. Chu, V. Sindhwani, Z. Ghahramani, and S. Keerthi. Relational Learning with Gaussian Processes. In NIPS, 2006.
10. M. Cissé, N. Usunier, T. Artières, and P. Gallinari. Robust Bloom Filters for Large MultiLabel Classification Tasks. In NIPS, pages 1851-1859, 2013.
11. A. Esuli and F. Sebastiani. Active Learning Strategies for Multi-Label Text Classification. In ECIR, 2009.
12. C.-S. Feng and H.-T. Lin. Multi-label Classification with Error-Correcting Codes. JMLR, pages 289-295, 2011.
13. A. Goldberg, X. Zhu, A. Furger, and J. Xu. OASIS: Online Active Semi-Supervised Learning. In AAAI, 2011.
14. A. Gretton, R. Herbrich, and A. Hyvärinen. Kernel methods for measuring independence. JMLR, 2005.
15. D. Hsu, S. Kakade, J. Langford, and T. Zhang. Multi-Label Prediction via Compressed Sensing. In NIPS, 2009.
16. S. Ji, L. Tang, S. Yu, and J. Ye. Extracting Shared Subspace for Multi-label Classification. In KDD, pages 381-389, 2008.
17. A. Kapoor, R. Viswanathan, and P. Jain. Multilabel Classification using Bayesian Compressed Sensing. In NIPS, 2012.
18. A. Krause and C. Guestrin. Near-optimal Nonmyopic Value of Information in Graphical Models. In UAI, 2005.
19. A. Krause, A. Singh, and C. Guestrin. Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies. JMLR, 2008.
20. X. Li and Y. Guo. Active Learning with Multi-label SVM Classification. In IJCAI, 2013.
21. X. Li, L. Wang, and E. Sung. Multi-label SVM Active Learning for Image Classification. In ICIP, 2004.
22. G. Nemhauser, L. Wolsey, and M. Fisher. An analysis of approximations for maximizing submodular set functions. Mathematical Programming, 1978.
23. J. C. Platt. Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods. In Advances In Large Margin Classifiers. MIT Press, 1999.
24. B. Settles. Active learning literature survey. Technical report, 2010.
25. Shihao, Y. Xue, and L. Carin. Bayesian Compressive Sensing , 2007.
26. A. Singh, A. Krause, C. Guestrin, and W. J. Kaiser. Efficient Informative Sensing using Multiple Robots.
27. M. Singh, E. Curran, and P. Cunningham. Active learning for multi-label image annotation. Technical report, University College Dublin, 2009.
28. F. Tai and H.-T. Lin. Multi-label Classification with Principal Label Space Transformation. In Workshop proceedings of learning from multi-label data, 2010.
29. J. Weston, S. Bengio, and N. Usunier. Wsabie: Scaling Up To Large Vocabulary Image Annotation. In IJCAI, 2011.
30. J. Weston, A. Makadia, and H. Yee. Label Partitioning for Sublinear Ranking. In ICML, 2013.
31. B. Yang, J. Sun, T. Wang, and Z. Chen. Effective multi-label active learning for text classification. In KDD, 2009.
32. H.-F. Yu, P. Jain, and I. S. Dhillon. Large-scale Multi-label Learning with Missing Labels. ICML, 2014.
33. Y. Zhang and J. G. Schneider. Multi-Label Output Codes using Canonical Correlation Analysis. In AISTATS, pages 873-882, 2011.
34. X. Zhu, J. Lafferty, and Z. Ghahramani. Semi-Supervised Learning: From Gaussian Fields to Gaussian Processes. Technical report, School of CS, CMU, 2003.