ML Anthology

Learning Markov Chains with Variable Memory Length from Noisy Output

Dana Angluin, Miklós Csürös
COLT 1997 pp. 298-308
doi:10.1145/267460.267517 /colt/1997/angluin1997colt-learning/

Abstract

Article Free Access Share on Learning Markov chains with variable memory length from noisy output Authors: Dana Angluin Department of Computer Science, Yale University, P.O Box 208285, New Haven CT Department of Computer Science, Yale University, P.O Box 208285, New Haven CTView Profile , Miklós Csűrös Department of Computer Science, Yale University, P.O Box 208285, New Haven CT Department of Computer Science, Yale University, P.O Box 208285, New Haven CTView Profile Authors Info & Claims COLT '97: Proceedings of the tenth annual conference on Computational learning theoryJuly 1997 Pages 298–308https://doi.org/10.1145/267460.267517Online:01 July 1997Publication History 7citation425DownloadsMetricsTotal Citations7Total Downloads425Last 12 Months5Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited. To manage your alert preferences, click on the button below. Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

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Text

Angluin and Csürös. "Learning Markov Chains with Variable Memory Length from Noisy Output." Annual Conference on Computational Learning Theory, 1997. doi:10.1145/267460.267517

Markdown

[Angluin and Csürös. "Learning Markov Chains with Variable Memory Length from Noisy Output." Annual Conference on Computational Learning Theory, 1997.](https://mlanthology.org/colt/1997/angluin1997colt-learning/) doi:10.1145/267460.267517

BibTeX

@inproceedings{angluin1997colt-learning,
  title     = {{Learning Markov Chains with Variable Memory Length from Noisy Output}},
  author    = {Angluin, Dana and Csürös, Miklós},
  booktitle = {Annual Conference on Computational Learning Theory},
  year      = {1997},
  pages     = {298-308},
  doi       = {10.1145/267460.267517},
  url       = {https://mlanthology.org/colt/1997/angluin1997colt-learning/}
}