Please use this identifier to cite or link to this item:
|Title:||A maximum margin discriminative learning algorithm for temporal signals||Authors:||Xu, W.
|Issue Date:||2006||Citation:||Xu, W., Wu, J., HUANG ZHIYONG (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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.