Sparse feature extraction using generalised partial least squares

Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing, MLSP 2006

Volumn , Issue , 2006, Pages 27-32

  Dhanjal, Charanpal ^a   Gunn, Steve R ^a   Shawe Taylor, John ^a  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATION THEORY; SUPPORT VECTOR MACHINES;

BOOSTED LATENT FEATURES (BLF); GENERALISED PARTIAL LEAST SQUARES; KERNEL BOOSTING; SPARSE MAXIMAL ALIGNMENT (SMA); SPARSE MAXIMAL COVARIANCE (SMC);

FEATURE EXTRACTION;

EID: 38949207177     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2006.275558     Document Type: Conference Paper

References (11)

1. Harold Hotelling, "Analysis of a complex of statistical variables into principle components," Journal of Educational Psychology, vol. 24, pp. 417-441 and 498-520, 1933.
2. Herman Wold, "Estimation of principal components and related models by iterative least squares," Multivariate analysis, pp. 391-420, 1966.
3. Michinari Momma and Kristin P. Bennett, "Constructing orthogonal latent features for arbitrary loss," in Feature Extraction, Foundations and Applications, Masoud Nikravesh Isabelle Guyon, Steve Gunn and Lofti Zadeh, Eds. Springer, 2005.
4. Nello Cristianini, John Shawe-Taylor, André Elisseeff, and Jaz S. Kandola, "On kernel-target alignment," in Advances in Neural Information Processing Systems, 2001, pp. 367-373.
5. Koby Crammer, Joseph Keshet, and Yoram Singer, "Kernel design using boosting," in Advances in Neural Information Processing Systems, 2002, pp. 537-544.
6. Michinari Momma and Kristin P. Bennett, "Sparse kernel partial least squares regression," in Proceedings of the Sixteenth Annual Conference on Learning Theory, 2003, pp. 216-230.
7. Michinari Momma, "Efficient computations via scalable sparse kernel partial least squares and boosted latent features," in Proceedings of the ACM International Conference on Knowledge Discovery in Data mining, New York, NY, USA, 2005, pp. 654-659, ACM Press.
8. John Shawe-Taylor and Nello Cristianini, Kernel Methods for Pattern Analysis, Cambridge University Press, New York, NY, USA, 2004.
9. Bernhard Schoelkopf, Alexander Smola, and Klaus-Robert Müller, "Nonlinear component analysis as a kernel eigenvalue problem," Neural Computation, vol. 10, no. 5, pp. 1299-1319, 1998.
10. Roman Rosipal and Leonard J. Trejo, "Kernel partial least squares regression in reproducing kernel hilbert space," Journal of Machine Learning Research, vol. 2, pp. 97-123, 2001.
11. Mark Stevenson Tony Rose and Miles Whitehead, "The reuters corpus volume 1 - from yesterday's news to tomorrow's language resources," in Proceedings of LREC-02, 3rd International Conference on Language Resources and Evaluation, 2002, pp. 827-832.