Sparse orthonormalized partial least squares

Belgian/Netherlands Artificial Intelligence Conference

Volumn , Issue , 2010, Pages

  van Gerven, Marcel ^a   Heskes, Tom ^a  

^a RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

COUPLING CONSTRAINTS; ELASTIC NET; PARTIAL LEAST SQUARE (PLS); PRIMARY VISUAL CORTEX; RECONSTRUCTION ERROR;

ALGORITHMS; ARTIFICIAL INTELLIGENCE;

LOADING;

EID: 84874003156     PISSN: 15687805     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. F. R. Bach and M. I. Jordan. Kernel independent component analysis. Journal of Machine Learning Research, 3:1-48, 2002.
2. H. Chun and S. Keleş. Sparse partial least squares regression for simultaneous dimension reduction and variable selection. Journal Of The Royal Statistical Society Series B, 72(1):3-25, 2010.
3. J. Friedman, T. Hastie, and R. Tibshirani. Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software, 33(1):1-22, 2010.
4. Y. Fujiwara, Y. Miyawaki, and Y. Kamitani. Estimating image bases for visual image reconstruction from human brain activity. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I.Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, pages 576-584. 2009.
5. D. R. Hardoon and J. Shawe-Taylor. Sparse canonical correlation analysis. In Sparsity and Inverse Problems in Statistical Theory and Econometrics Workshop, 2008.
6. D. Hassabis, C. Chu, G. Rees, N. Weiskopf, P. D. Molyneux, and E. A. Maguire. Decoding neuronal ensembles in the human hippocampus. Current Biology, 19:546-554, 2009.
7. H. Hotelling. Relations between two sets of variates. Biometrika, 28:312-377, 1936.
8. T. M. Mitchell, S. V. Shinkareva, A. Carlson, K.-M. Chang, V. L. Malave, R. A. Mason, and M. A. Just. Predicting human brain activity associated with the meanings of nouns. Science, 320(5880):1191-1195, 2008.
9. Y. Miyawaki, H. Uchida, O. Yamashita, M. Sato, Y. Morito, H. C. Tanabe, N. Sadato, and Y. Kamitani. Visual image reconstruction from human brain activity using a combination of multiscale local image decoders. Neuron, 60(5):915-929, 2008.
10. T. Naselaris, R. J. Prenger, K. N. Kay, M. Oliver, and J. L. Gallant. Bayesian reconstruction of natural images from human brain activity. Neuron, 63(6):902-915, 2009.
11. R. Rosipal and N. Krämer. Overview and recent advances in partial least squares. In SLSFS, pages 34-51, 2005.
12. S. Roweis and C. Brody. Linear heteroencoders. Technical Report GCNU TR 1999-002, Gatsby Computational Neuroscience Unit, 1999.
13. C. Saunders, M. Grobelnik, S. R. Gunn, and J. Shawe-Taylor, editors. Subspace, Latent Structure and Feature Selection, Statistical and Optimization, Perspectives Workshop, volume 3940 of Lecture Notes in Computer Science, Bohinj, Slovenia, 2006. Springer.
14. R. Tibshirani, M. Saunders, S. Rosset, J. Zhu, and K. Knight. Sparsity and smoothness via the fused lasso. J. R. Statist. Soc. B, 67(1):91-108, 2005.
15. M. E. Tipping and C. M. Bishop. Probabilistic principal component analysis. Journal of the Royal Statistical Society, Series B, 61(3):611-622, 1999.
16. C. Wang. Variational Bayesian approach to canonical correlation analysis. IEEE Trans Neural Netw, 18:905-910, 2007.
17. H. Zou and T. Hastie. Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society B, 67(2):301-320, 2005.
18. H. Zou, T. Hastie, and R. Tibshirani. Sparse principal component analysis. Journal of Computational and Graphical Statistics, 15(2):265-286, 2006.