Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICPR.2006.96
Title: A maximum margin discriminative learning algorithm for temporal signals
Authors: Xu, W.
Wu, J.
Huang, Z. 
Issue Date: 2006
Source: Xu, W.,Wu, J.,Huang, Z. (2006). A maximum margin discriminative learning algorithm for temporal signals. Proceedings - International Conference on Pattern Recognition 2 : 460-463. ScholarBank@NUS Repository. https://doi.org/10.1109/ICPR.2006.96
Abstract: We propose a new maximum margin discriminative learning algorithm here for classification of temporal signals. It is superior to conventional HMM in the sense that it does not need prior knowledge of the data distribution. It learns the classifier by using a nonlinear discriminative procedure based on a maximum margin criterion, providing a strong generalization mechanism. This maximum margin discriminative learning method is presented together with a two-step learning algorithm. We evaluate the kernel based hidden Markov model by applying it to some simulation and real experiments. The preliminary results have shown significant improvement in classification accuracy. © 2006 IEEE.
Source Title: Proceedings - International Conference on Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/40489
ISBN: 0769525210
ISSN: 10514651
DOI: 10.1109/ICPR.2006.96
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