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Global PAC Bounds for Learning Discrete Time Markov Chains
Learning models from observations of a system is a powerful tool with many applications. In this paper, we consider learning Discrete Time Markov Chains (DTMC), with different methods such as frequency estimation or Laplace smoothing. While models learnt with such methods converge asymptotically tow...
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| 出版年: | Computer Aided Verification |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7363184/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-53291-8_17 |
| タグ: |
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