Contractive rectifier networks for nonlinear maximum margin classification

Senjian An, Munawar Hayat, Salam Khan, Mohammed Bennamoun, Farid Boussaid, Ferdous Sohel

Research output: A Conference proceeding or a Chapter in BookConference contribution

4 Citations (Scopus)
2 Downloads (Pure)

Abstract

To find the optimal nonlinear separating boundary with maximum margin in the input data space, this paper proposes Contractive Rectifier Networks (CRNs), wherein the hidden-layer transformations are restricted to be contraction mappings. The contractive constraints ensure that the achieved separating margin in the input space is larger than or equal to the separating margin in the output layer. The training of the proposed CRNs is formulated as a linear support vector machine (SVM) in the output layer, combined with two or more contractive hidden layers. Effective algorithms have been proposed to address the optimization challenges arising from contraction constraints. Experimental results on MNIST, CIFAR-10, CIFAR-100 and MIT-67 datasets demonstrate that the proposed contractive rectifier networks consistently outperform their conventional unconstrained rectifier network counterparts
Original languageEnglish
Title of host publication2015 International Conference on Computer Vision, ICCV 2015
EditorsRuzena Bajcsy, Greg Hager, Yi Ma
Place of PublicationSantiago
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages2515-2523
Number of pages9
ISBN (Electronic)9781467383912
ISBN (Print)9781467383912
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event2015 IEEE International Conference on Computer Vision - Santiago, Santiago, Chile
Duration: 11 Dec 201518 Dec 2015

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
Volume2015 International Conference on Computer Vision, ICCV 2015
ISSN (Print)1550-5499

Conference

Conference2015 IEEE International Conference on Computer Vision
Abbreviated titleICCV 2015
CountryChile
CitySantiago
Period11/12/1518/12/15

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Cite this

An, S., Hayat, M., Khan, S., Bennamoun, M., Boussaid, F., & Sohel, F. (2015). Contractive rectifier networks for nonlinear maximum margin classification. In R. Bajcsy, G. Hager, & Y. Ma (Eds.), 2015 International Conference on Computer Vision, ICCV 2015 (pp. 2515-2523). [7410646] (Proceedings of the IEEE International Conference on Computer Vision; Vol. 2015 International Conference on Computer Vision, ICCV 2015). Santiago: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/iccv.2015.289