Transduction with matrix completion: Three birds with one stone

Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, NIPS 2010

Volumn , Issue , 2010, Pages

  Goldberg, Andrew B ^a   Zhu, Xiaojin ^a   Recht, Benjamin ^a   Xu, Jun Ming ^a   Nowak, Robert ^b  

^a University of Wisconsin   (United States)

^b UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACTERIOPHAGES; LEARNING SYSTEMS;

FIXED POINT CONTINUATIONS; LOSS FUNCTIONS; MATRIX; MATRIX COMPLETION; MATRIX COMPLETION PROBLEMS; MINIMIZATION PROBLEMS; MISSING DATA; MULTI-LABEL LEARNING; NUCLEAR NORM MINIMIZATIONS; REAL-WORLD TASK;

MATRIX ALGEBRA;

EID: 85162074163     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Andreas Argyriou, Charles A. Micchelli, and Massimiliano Pontil. On spectral learning. Journal of Machine Learning Research, 11:935-953, 2010.
2. Emmanuel J. Candès and Benjamin Recht. Exact matrix completion via convex optimization. Foundations of Computational Mathematics, 9:717-772, 2009.
3. Emmanuel J. Candès and Terence Tao. The power of convex relaxation: Near-optimal matrix completion. IEEE Transactions on Information Theory, 56:2053-2080, 2010.
4. Olivier Chapelle, Alexander Zien, and Bernhard Schölkopf, editors. Semi-supervised learning. MIT Press, 2006.
5. André Elisseeff and Jason Weston. A kernel method for multi-labelled classification. In Thomas G. Dietterich, Suzanna Becker, and Zoubin Ghahramani, editors, NIPS, pages 681- 687. MIT Press, 2001.
6. Zoubin Ghahramani and Michael I. Jordan. Supervised learning from incomplete data via an EM approach. In Advances in Neural Information Processing Systems 6, pages 120-127. Morgan Kaufmann, 1994.
7. Daniel Hsu, Sham Kakade, John Langford, and Tong Zhang. Multi-label prediction via compressed sensing. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, pages 772-780. 2009.
8. Shuiwang Ji, Lei Tang, Shipeng Yu, and Jieping Ye. Extracting shared subspace for multi-label classification. In KDD '08: Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 381-389, New York, NY, USA, 2008. ACM.
9. Roderick J. A. Little and Donald B. Rubin. Statistical Analysis with Missing Data. Wiley- Interscience, 2nd edition, September 2002.
10. Shiqian Ma, Donald Goldfarb, and Lifeng Chen. Fixed point and Bregman iterative methods for matrix rank minimization. Mathematical Programming Series A, to appear (published online September 23, 2009).
11. Guillaume Obozinski, Ben Taskar, and Michael I. Jordan. Joint covariate selection and joint subspace selection for multiple classification problems. Statistics and Computing, 20(2):231-252, 2010.
12. Piyush Rai and Hal Daume. Multi-label prediction via sparse infinite CCA. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, pages 1518-1526. 2009.
13. Nathan Srebro and Adi Shraibman. Rank, trace-norm and max-norm. In Proceedings of the 18th Annual Conference on Learning Theory, pages 545-560. Springer-Verlag, 2005.
14. K. Trohidis, G. Tsoumakas, G. Kalliris, and I. Vlahavas. Multilabel classification of music into emotions. In Proc. 9th International Conference on Music Information Retrieval (ISMIR 2008), Philadelphia, PA, USA, 2008, 2008.
15. G. Tsoumakas, I. Katakis, and I. Vlahavas. Mining multi-label data. In Data Mining and Knowledge Discovery Handbook. Springer, 2nd edition, 2010.
16. Xiaojin Zhu and Andrew B. Goldberg. Introduction to Semi-Supervised Learning. Morgan & Claypool, 2009.