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發(fā)表于 2025-3-21 16:50:50 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Grammatical Inference: Algorithms and Applications
編輯Alexander Clark,Fran?ois Coste,Laurent Miclet
視頻videohttp://file.papertrans.cn/388/387813/387813.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: ;
出版日期Conference proceedings 2008
版次1
doihttps://doi.org/10.1007/978-3-540-88009-7
isbn_softcover978-3-540-88008-0
isbn_ebook978-3-540-88009-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 21:59:46 | 只看該作者
,Mensch-Maschine-Systeme für die Planung,c linear languages and show the probabilistic learnability with membership queries in polynomial time. This learnability is derived from an exact learning algorithm for this subclass with membership queries, equivalence queries and a representative sample.
板凳
發(fā)表于 2025-3-22 02:58:59 | 只看該作者
Umsetzungsbeispiele und Lessons Learned, the relations existing between different models of correction queries, as well as their connection to other well-known Gold-style and query learning models. The study comprises results obtained in the general case when time complexity issues are ignored, and in the restricted case when efficiency c
地板
發(fā)表于 2025-3-22 05:17:09 | 只看該作者
Polynomial Time Probabilistic Learning of a Subclass of Linear Languages with Queriesc linear languages and show the probabilistic learnability with membership queries in polynomial time. This learnability is derived from an exact learning algorithm for this subclass with membership queries, equivalence queries and a representative sample.
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發(fā)表于 2025-3-22 09:58:20 | 只看該作者
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發(fā)表于 2025-3-22 15:25:54 | 只看該作者
https://doi.org/10.1007/978-3-322-90632-8mmutative regular languages from positive and negative samples, and we show, from experimental results, that far from being a theoretical algorithm, it produces very high recognition rates in comparison with classical inference algorithms.
7#
發(fā)表于 2025-3-22 20:47:27 | 只看該作者
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發(fā)表于 2025-3-22 23:04:55 | 只看該作者
https://doi.org/10.1007/978-3-642-58802-0ich is an unconventional model of computation based on biomolecules (.). We prove that a subclass of context-sensitive languages can be inferred by using the representation result in combination with reductions from linear languages to .-testable in the strict sense regular languages.
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發(fā)表于 2025-3-23 03:29:28 | 只看該作者
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發(fā)表于 2025-3-23 06:05:32 | 只看該作者
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