Large-scale dictionary learning for local coordinate coding

British Machine Vision Conference, BMVC 2010 - Proceedings

Volumn , Issue , 2010, Pages

  Xie, Bo ^a   Song, Mingli ^b   Tao, Dacheng ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b ZHEJIANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; OBJECT RECOGNITION;

CODING METHODS; DICTIONARY LEARNING; LARGE-SCALE DATABASE; LOCAL COORDINATE; NUMBER OF SAMPLES; ONLINE LEARNING ALGORITHMS; RANDOM SAMPLE; VISUAL FEATURE;

COMPUTER VISION;

EID: 84898440793     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/C.24.36     Document Type: Conference Paper

References (14)

1. Michal Aharon, Michael Elad, and Alfred Bruckstein. K-svd: An algorithm for designing overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing, 54(11):4311-4322, 2006.
2. Leon Bottou and Olivier Bousquet. The tradeoffs of large scale learning. In J.C. Platt, D. Koller, Y. Singer, and S. Roweis, editors, Advances in Neural Information Processing Systems 20, pages 161-168. MIT Press, Cambridge, MA, 2008.
3. Chih-Chung Chang and Chih-Jen Lin. LIBSVM: a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.
4. Mark Everingham, Luc Van Gool, Chris Williams, and Andrew Zisser-man. The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results. URL http://www.pascal-network.org/challenges/VOC/voc2007/workshop/index.html.
5. Gregory Griffin, Alex Holub, and Pietro Perona. Caltech-256 object category dataset. Technical Report 7694, California Institute of Technology, 2007. URL http://authors.library.caltech.edu/7694.
6. Julien Mairal, Francis Bach, Jean Ponce, and Guillermo Sapiro. Online dictionary learning for sparse coding. In ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning, pages 689-696, New York, NY, USA, 2009. ACM. ISBN 978-1-60558-516-1.
7. Joseph F. Murray and Kenneth Kreutz-Delgado. Learning sparse overcomplete codes for images. J. VLSI Signal Process. Syst., 46(1):1-13, 2007. ISSN 0922-5773.
8. David Nister and Henrik Stewenius. Scalable recognition with a vocabulary tree. In Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 2161-2168, Washington, DC, USA, 2006. IEEE Computer Society. ISBN 0-7695-2597-0.
9. Eric Nowak, Frédéric Jurie, and Bill Triggs. Sampling strategies for bag-of-features image classification. In European Conference on Computer Vision. Springer, 2006. URL http://lear.inrialpes.fr/pubs/2006/NJT06.
10. Karl Sjöstrand. Matlab implementation of LASSO, LARS, the elastic net and SPCA, jun 2005. URL http://www2.imm.dtu.dk/pubdb/p.php?3897.Version 2.0.
11. Robert Tibshirani. Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society (Series B), 58:267-288, 1996.
12. Jianchao Yang, Kai Yu, Yihong Gong, and Thomas S. Huang. Linear spatial pyramid matching using sparse coding for image classification. In CVPR, pages 1794-1801. IEEE, 2009.
13. Kai Yu, Tong Zhang, and Yihong Gong. Nonlinear learning using local coordinate coding. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, pages 2223-2231. 2009.
14. Tianyi Zhou and Dacheng Tao. Fast gradient clustering. NIPS 2009 Workshop on Discrete Optimization in Machine Learning: Submodularity, Sparsity & Polyhedra (NIPS: DISCML), pages 1-6, 2009.