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Learning structured dictionary based on inter-class similarity and representative margins

Conference Paper


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Abstract


  • We consider the problem of learning a structured and discriminative dictionary based on sparse representation for classification task. The structure comprises class-shared and class-specific partitions which allows the separation of common and class-specific information in the data for classification. The resulting optimization problem was a max margin formulation that exploits the hinge loss function property. Comparative evaluation of the proposed classifier against four recent alternatives in a gender classification task indicates a 3-percenatge point improvement.

Publication Date


  • 2016

Citation


  • Zhang, Y., Ogunbona, P. O., Li, W. & Wallace, G. G. (2016). Learning structured dictionary based on inter-class similarity and representative margins. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 2399-2403). United States: IEEE.

Scopus Eid


  • 2-s2.0-84973326560

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=6470&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5442

Start Page


  • 2399

End Page


  • 2403

Place Of Publication


  • United States

Abstract


  • We consider the problem of learning a structured and discriminative dictionary based on sparse representation for classification task. The structure comprises class-shared and class-specific partitions which allows the separation of common and class-specific information in the data for classification. The resulting optimization problem was a max margin formulation that exploits the hinge loss function property. Comparative evaluation of the proposed classifier against four recent alternatives in a gender classification task indicates a 3-percenatge point improvement.

Publication Date


  • 2016

Citation


  • Zhang, Y., Ogunbona, P. O., Li, W. & Wallace, G. G. (2016). Learning structured dictionary based on inter-class similarity and representative margins. 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 2399-2403). United States: IEEE.

Scopus Eid


  • 2-s2.0-84973326560

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=6470&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5442

Start Page


  • 2399

End Page


  • 2403

Place Of Publication


  • United States