Parallel stochastic grammar induction
This paper examines the problem of stochastic grammar induction and gives a formal analysis of observed limitations of a classical algorithm. It then describes a parallel approach to the problem which avoids these limitations. Finally, a proof is presented which shows that a popular training algorit...
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| container_end_page | 1428 vol.3 |
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| container_volume | 3 |
| creator | Kremer, S.C. |
| description | This paper examines the problem of stochastic grammar induction and gives a formal analysis of observed limitations of a classical algorithm. It then describes a parallel approach to the problem which avoids these limitations. Finally, a proof is presented which shows that a popular training algorithm already in use for recurrent connectionist networks implements the new approach. |
| doi_str_mv | 10.1109/ICNN.1997.614003 |
| format | Conference Proceeding |
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| identifier | ISBN: 0780341228 |
| ispartof | Proceedings of International Conference on Neural Networks (ICNN'97), 1997, Vol.3, p.1424-1428 vol.3 |
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| language | eng |
| recordid | cdi_ieee_primary_614003 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithm design and analysis Bayesian methods Character generation Distributed computing Frequency Gold Induction generators Learning systems Stochastic processes Stochastic systems |
| title | Parallel stochastic grammar induction |
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