DocumentCode
2919395
Title
MKPM: A multiclass extension to the kernel projection machine
Author
Takerkart, Sylvain ; Ralaivola, Liva
Author_Institution
Inst. de Neurosciences Cognitives de la Mediterranee, Aix-Marseille Univ., Marseille, France
fYear
2011
fDate
20-25 June 2011
Firstpage
2785
Lastpage
2791
Abstract
We introduce Multiclass Kernel Projection Machines (MKPM), a new formalism that extends the Kernel Projection Machine framework to the multiclass case. Our formulation is based on the use of output codes and it implements a co-regularization scheme by simultaneously constraining the projection dimensions associated with the individual predictors that constitute the global classifier. In order to solve the optimization problem posed by our formulation, we propose an efficient dynamic programming approach. Numerical simulations conducted on a few pattern recognition problems illustrate the soundness of our approach.
Keywords
dynamic programming; pattern classification; MKPM; dynamic programming approach; multiclass extension; multiclass kernel projection machine; optimization problem; pattern recognition problem; Dynamic programming; Encoding; Kernel; Machine learning; Minimization; Numerical simulation; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
Conference_Location
Providence, RI
ISSN
1063-6919
Print_ISBN
978-1-4577-0394-2
Type
conf
DOI
10.1109/CVPR.2011.5995657
Filename
5995657
Link To Document