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ICML
2009
IEEE

Large margin training for hidden Markov models with partially observed states

13 years 12 days ago
Large margin training for hidden Markov models with partially observed states
Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non-convexity of the optimization problem, previous works usually rely on severe approximations so that it is still an open problem. We propose a new learning algorithm that relies on non-convex optimization and bundle methods and allows tackling the original optimization problem as is. It is proved to converge to a solution with accuracy with a rate O(1/ ). We provide experimental results gained on speech and handwriting recognition that demonstrate the potential of the method.
Thierry Artières, Trinh Minh Tri Do
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2009
Where ICML
Authors Thierry Artières, Trinh Minh Tri Do
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