Adaptive and Weighted Collaborative Representations for image classification

Pattern Recognition Letters

Volumn 43, Issue 1, 2014, Pages 127-135

  Timofte, Radu ^a   Van Gool, Luc ^a,b  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b ETH ZURICH   (Switzerland)

Author keywords

Classification; Collaborative Representation; Kernel; Ridge Regression; Sparse Representation

Indexed keywords

CLASSIFICATION (OF INFORMATION); FACE RECOGNITION; REGRESSION ANALYSIS;

ALGEBRAIC SOLUTION; CLASSIFICATION CONFIDENCE; CLASSIFICATION PERFORMANCE; COLLABORATIVE REPRESENTATIONS; KERNEL; REGULARIZED LEAST SQUARES; RIDGE REGRESSION; SPARSE REPRESENTATION;

IMAGE CLASSIFICATION;

EID: 84899411681     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2013.08.010     Document Type: Article

References (32)

1. A. Bruckstein, D. Donoho, and M. Elad From sparse solutions of systems of equations to sparse modeling of signals and images SIAM Review 51 1 2009 34 81
2. Cai, D., He, X., Han, J. 2007. Efficient kernel discriminant analysis via spectral regression. In: International Conference on Data Mining (ICDM'07).
3. Z.J. Daye, and X.J. Jeng Shrinkage and model selection with correlated variables via weighted fusion Computational Statistics and Data Analysis 53 4 2009 1284 1298
4. B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani Least angle regression The Annals of Statistics 32 2 2004 407 499 (Pubitemid 41250302)
5. R. Fisher The statistical utilization of multiple measurements Annals of Eugenics 8 1938 376 386
6. G.H. Fu, and Q.S. Xu Grouping variable selection by weight fused elastic net for multi-collinear data Communications in Statistics - Simulation and Computation 41 2 2012 205 221
7. Grave, E., Obozinski, G., Bach, F. 2011. Trace lasso: a trace norm regularization for correlated designs. In. Advances in Neural Information Processing Systems (NIPS), pp. 2187-2195.
8. l 1-regularized least squares IEEE Journal of Selected Topics in Signal Processing 1 4 2007 606 617 (Pubitemid 351266626)
9. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner Gradient-based learning applied to document recognition Proceedings of the IEEE 86 11 1998 2278 2324
10. H. Lee, A. Battle, R. Raina, and A.Y. Ng Efficient sparse coding algorithms B. Schölkopf, J.C. Platt, T. Hoffman, NIPS 2006 MIT Press 801 808
11. R.J.A. Little, and D.B. Rubin Statistical Analysis with Missing Data second ed. 2002 John Wiley & Sons, Inc
12. Lorbert, A., Eis, D., Kostina, V., Blei, D.M., Ramadge, P.J. 2010. Exploiting covariate similarity in sparse regression via the pairwise elastic net. In: JMLR - Proceedings of the 13th International Conference on Artificial Intelligence and Statistics, vol. 9, pp. 477-484.
13. Martinez, A., Benavente, R. 1998. The AR face database. Technical Report; CVC Tech. Report No. 24.
14. R. Penrose A generalized inverse for matrices Mathematical Proceedings of the Cambridge Philosophical Society 51 1955 406 413
15. Saunders, C., Gammerman, A., Vovk, V. 1998. Ridge regression learning algorithm in dual variables. In: Proc. of the 15th Int. Conf. on Machine Learning (ICML-98), Madison, Wisconsin, pp. 515-521.
16. B. Schölkopf, and A.J. Smola Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond 2001 The MIT Press
17. Stallkamp, J., Schlipsing, M., Salmen, J., Igel, C. 2011. The German traffic sign recognition benchmark: a multi-class classification competition. In: International Joint Conference on Neural Networks (IJCNN).
18. J. Suykens, and J. Vandewalle Least squares support vector machine classifiers Neural Processing Letters 9 3 1999 293 300
19. R. Tibshirani Regression shrinkage and selection via the lasso Journal of the Royal Statistical Society, Series B 58 1 1996 267 288
20. A.N. Tikhonov, and V.Y. Arsenin Solution of Ill-posed Problems 1977 Winston & Sons
21. Timofte, R., Van Gool, L.J. 2012a. Iterative nearest neighbors for classification and dimensionality reduction. In: IEEE Conference on Computer Vision and, Pattern Recognition (CVPR), pp. 2456-2463.
22. Timofte, R., Van Gool, L.J. 2011. Sparse representation based projections. In: British Machine Vision Conference (BMVC).
23. R. Timofte, and L.J. Van Gool Weighted collaborative representation and classification of images International Conference on Pattern Recognition (ICPR) 2012 IEEE 1606 1610
24. l 2-minimization approach Pattern Recognition Letters 34 2013 201 208
25. J. Wright, A.Y. Yang, A. Ganesh, S.S. Sastry, and Y. Ma Robust face recognition via sparse representation IEEE Transactions on Pattern Analysis and Machine Intelligence 31 2 2009 210 227
26. Yang, M., Zhang, L., Zhang, D., Wang, S. 2012. Relaxed collaborative representation for pattern classification. In: IEEE Conference on Computer Vision and, Pattern Recognition (CVPR), pp. 2224-2231.
27. M. Yuan, and Y. Lin Model selection and estimation in regression with grouped variables Journal of the Royal Statistical Society: Series B (Statistical Methodology) 68 1 2006 49 67 (Pubitemid 43415335)
28. Zhang, L., Yang, M., Feng, X. 2011. Sparse representation or collaborative representation: which helps face recognition? In: ICCV.
29. L. Zhang, W.D. Zhou, P.C. Chang, J. Liu, Z. Yan, T. Wang, and F.Z. Li Kernel sparse representation-based classifier IEEE Transactions on Signal Processing 60 4 2012 1684 1695
30. H. Zou The adaptive lasso and its oracle properties Journal of the American Statistical Association 101 476 2006 1418 1429
31. H. Zou, and T. Hastie Regularization and variable selection via the elastic net Journal of the Royal Statistical Society: Series B (Statistical Methodology) 67 2 2005 301 320 (Pubitemid 40465877)
32. H. Zou, and H.H. Zhang On the adaptive elastic-net with a diverging number of parameters Annals of Statistics 37 4 2009 1733 1751