Online learning for multi-task feature selection

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2010, Pages 1693-1996

  Yang, Haiqin ^a   King, Irwin ^a   Lyu, Michael R ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Dual averaging method; Feature selection; Multi task learning; Online learning; Supervised learning

Indexed keywords

AVERAGING METHOD; CLOSED FORM SOLUTIONS; DATA SETS; FEATURE SELECTION; MEMORY COST; MULTITASK LEARNING; ON-LINE ALGORITHMS; ONLINE LEARNING; REAL-WORLD; TIME COMPLEXITY; TRAINING DATA;

ALGORITHMS; E-LEARNING; KNOWLEDGE MANAGEMENT; SUPERVISED LEARNING;

FEATURE EXTRACTION;

EID: 78651304213     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1871437.1871706     Document Type: Conference Paper

References (15)

1. A. Argyriou, T. Evgeniou, and M. Pontil. Convex multi-task feature learning. Machine Learning, 73(3):243-272, 2008.
2. B. Bakker and T. Heskes. Task clustering and gating for bayesian multitask learning. Journal of Machine Learning Research, 4:83-99, 2003.
3. S. Balakrislman and D. Madigan. Algorithms for sparse linear classifiers in the massive data setting. Journal of Machine Learning Research, 9:313-337, 2008.
4. S. Ben-David and R. Schuller. Exploiting task relatedness for mulitple task learning. In COLT, pages 567-580, 2003.
5. O. Dekel, P. M. Long, and Y. Singer. Online multitask learning. In COLT, pages 453-467, 2006.
6. J. Duchi and Y. Singer. Efficient learning using forward-backward splitting. Journal of Machine Learning Research, 10:2873-2898, 2009.
7. T. Evgeniou and M. Pontil. Regularized multi-task learning. In KDD, pages 109-117, 2004.
8. J. Langford, L. Li, and T. Zhang. Sparse online learning via truncated gradient. Journal of Machine Learning Research, 10:777-801, 2009.
9. 2,1 norm minimization. In UAI, 2009.
10. Y. Nesterov. Primal-dual subgradient methods for convex problems. Mathematical Programming, 120(1):221-259, 2009.
11. G. Obozinski, B. Taskar, and M. I. Jordan. Joint covariate selection and joint subspace selection for multiple classification problems. Statistics and Computing, 2009.
12. R. Tibshirani. Regression shrinkage and selection via the lasso. J. Roy. Statist. Soc. Ser. B, 58(1):267-288, 1996.
13. L. Xiao. Dual averaging method for regularized stochastic learning and online optimization. Technical Report MSR-TR-2009-100, Microsoft Research, 2009.
14. H. Yang, I. King, and M. R. Lyu. Multi-task learning for one-class classification. In IJCNN, Barcelona, Spain, 2010.
15. H. Yang, Z. Xu, I. King, and M. R. Lyu. Online learning for group lasso. In ICML, Haifa, Israel, 2010.