Instance Selection Using Two Phase Collaborative Neighbor Representation
Finding relevant instances in databases has always been a challenging task. Recently a new method, called Sparse Modeling Representative Selection (SMRS) has been proposed in this area and is based on data self-representation. SMRS estimates a matrix of coefficients by minimizing a reconstruction error and a regularization term on these coefficients using the L 1,q matrix norm. In this paper, we propose another alternative of coding based on a two stage Collaborative Neighbor Representation in which a non-dense matrix of coefficients is estimated without invoking any explicit sparse coding. Experiments are conducted on summarizing a video movie and on summarizing training face datasets used for face recognition. These experiments showed that the proposed method can outperform the state-of-the art methods.
KeywordsInstance selection collaborative neighbor representation video summarization classification
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- 4.Tropp, J.: Column subset selection, matrix factorization and eigenvalue optimization. In: Proc. of ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 978–986 (January 2009)Google Scholar
- 5.Boutsidis, C., Mahoney, M., Drineas, P.: An improved approximation algorithm for the column subset selection problem. In: Proc. of ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 968–977 (January 2009)Google Scholar
- 6.Elhamifar, E., Sapiro, G., Vidal, R.: See all by looking at a few: Sparse modeling for finding representative objects. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1600–1607 (June 2012)Google Scholar
- 7.Bien, J., Xu, Y., Mahoney, M.: CUR from a sparse optimization viewpoint. In: Advances in Neural Information Processing Systems, pp. 217–225 (December 2010)Google Scholar
- 8.Chan, T.: Rank revealing qr factorizations. Linear Algebra and its Applications 88–89, 67–82 (1987)Google Scholar
- 11.Givoni, I., Chung, C., Frey, B.: Hierarchical affinity propagation. In: Conference on Uncertainty in Artificial Intelligence (July 2011)Google Scholar
- 12.Duda, R., Hart, P., Stork, D.: Pattern Classification. Wiley-Interscience (2004)Google Scholar
- 13.Dueck, D., Frey, B.: Non-metric affinity propagation for unsupervised image categorization. In: Proc. of International Conference in Computer Vision, pp. 1–8 (October 2007)Google Scholar