書目名稱Grammatical Inference: Algorithms and Applications影響因子(影響力)學(xué)科排名
書目名稱Grammatical Inference: Algorithms and Applications網(wǎng)絡(luò)公開度
書目名稱Grammatical Inference: Algorithms and Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Grammatical Inference: Algorithms and Applications被引頻次
書目名稱Grammatical Inference: Algorithms and Applications被引頻次學(xué)科排名
書目名稱Grammatical Inference: Algorithms and Applications年度引用
書目名稱Grammatical Inference: Algorithms and Applications年度引用學(xué)科排名
書目名稱Grammatical Inference: Algorithms and Applications讀者反饋
書目名稱Grammatical Inference: Algorithms and Applications讀者反饋學(xué)科排名
作者: ABHOR 時(shí)間: 2025-3-21 21:59
,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.作者: 不能約 時(shí)間: 2025-3-22 02:58
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作者: 擁護(hù) 時(shí)間: 2025-3-22 05:17
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.作者: 閑蕩 時(shí)間: 2025-3-22 09:58 作者: 獸群 時(shí)間: 2025-3-22 15:25
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.作者: 獸群 時(shí)間: 2025-3-22 20:47 作者: 鼓掌 時(shí)間: 2025-3-22 23:04
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.作者: ear-canal 時(shí)間: 2025-3-23 03:29 作者: Soliloquy 時(shí)間: 2025-3-23 06:05 作者: Hallowed 時(shí)間: 2025-3-23 20:32 作者: conference 時(shí)間: 2025-3-23 23:11
State-Merging DFA Induction Algorithms with Mandatory Merge Constraints following the Abbadingo contest protocol illustrate the interest of using mandatory merge constraints. As a side effect, this paper also points out an interesting property of state-merging techniques: they can be extended to take any pair of DFAs as inputs rather than simple strings.作者: ENDOW 時(shí)間: 2025-3-24 02:38
Polynomial Distinguishability of Timed Automatathat deterministic time automata with two or more clocks are not polynomially distinguishable. As a consequence, they are not efficiently identifiable. Last but not least, we prove that deterministic timed automata with one clock are polynomially distinguishable, which makes them very likely to be efficiently identifiable in the limit.作者: Lignans 時(shí)間: 2025-3-24 07:10
,Wieviel Akzeptanz ertr?gt der Mensch?,s we concentrate here on two classes of languages, the topological balls of strings (for the edit distance) and the deterministic finite automata (.), and (re-)visit the different learning paradigms to sustain our claims.作者: Enthralling 時(shí)間: 2025-3-24 11:10
Relationale Existenzweisen von Maschinenct operation is dropped..Moreover, we define an algebraic structure, which is an extension of the string monoid, that allows the identification of any transduction that can be realized by finite state machines without empty-transitions.作者: 審問,審訊 時(shí)間: 2025-3-24 15:35 作者: 母豬 時(shí)間: 2025-3-24 20:58 作者: Myocyte 時(shí)間: 2025-3-24 23:32
https://doi.org/10.34157/978-3-648-15833-3 is based on a generalisation of distributional learning and uses the lattice of context occurrences. The formalism and the algorithm seem well suited to natural language and in particular to the modelling of first language acquisition.作者: 阻塞 時(shí)間: 2025-3-25 04:47
,Technik — Deutungen ihrer Entwicklung, normalised representation that can be used to generate trees from the underlying distribution. We also study some properties of consistency for rational stochastic tree languages and discuss their implication for the inference. We finally consider the applicability of .EES to trees built over an unranked alphabet.作者: Esalate 時(shí)間: 2025-3-25 09:34 作者: 培養(yǎng) 時(shí)間: 2025-3-25 13:16
Katja Kanzler,Brigitte Georgi-Findlayree languages of arbitrarily many dimensions. Via the correspondence between trees and string languages (“yield operation”) this is equivalent to the statement that this way even some string language classes beyond context-freeness have become learnable with respect to Angluin’s learning model as well.作者: 品牌 時(shí)間: 2025-3-25 19:52
,Musterl?sungen zu den übungen,to extract some nontrivial structure in the form of a PDFA with 30-50 states. An additional feature, in fact partly explaining the reduction in sample size, is that our algorithm does not need as input any information about the distinguishability of the target.作者: misanthrope 時(shí)間: 2025-3-25 21:27
A Polynomial Algorithm for the Inference of Context Free Languages is based on a generalisation of distributional learning and uses the lattice of context occurrences. The formalism and the algorithm seem well suited to natural language and in particular to the modelling of first language acquisition.作者: 躲債 時(shí)間: 2025-3-26 01:03 作者: 過份艷麗 時(shí)間: 2025-3-26 07:29 作者: 惹人反感 時(shí)間: 2025-3-26 10:23 作者: agnostic 時(shí)間: 2025-3-26 13:50
Towards Feasible PAC-Learning of Probabilistic Deterministic Finite Automatato extract some nontrivial structure in the form of a PDFA with 30-50 states. An additional feature, in fact partly explaining the reduction in sample size, is that our algorithm does not need as input any information about the distinguishability of the target.作者: 極肥胖 時(shí)間: 2025-3-26 17:18
Learning Commutative Regular Languagesmmutative 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.作者: fatuity 時(shí)間: 2025-3-26 23:07 作者: PRO 時(shí)間: 2025-3-27 01:36 作者: 領(lǐng)帶 時(shí)間: 2025-3-27 07:47 作者: 可商量 時(shí)間: 2025-3-27 11:44
Learning Meaning Before Syntaxge acquisition and by a desire to incorporate a robust notion of semantics in the field of Grammatical Inference. We argue that not only is it more natural to take into account semantics, but also that semantic information can make learning easier, and can give us a better understanding of the relat作者: intention 時(shí)間: 2025-3-27 15:21
Schema-Guided Induction of Monadic Querieste schema guidance into an RPNI-based learning algorithm, in which monadic queries are represented by pruning node selecting tree transducers. We present experimental results on schema guidance by the DTD of HTML.作者: 拖網(wǎng) 時(shí)間: 2025-3-27 17:55
A Polynomial Algorithm for the Inference of Context Free Languagesorithm uses a representation which we call Binary Feature Grammars based on a set of features, capable of representing richly structured context free languages as well as some context sensitive languages. More precisely, we focus on a particular case of this representation where the features corresp作者: OTHER 時(shí)間: 2025-3-28 00:40 作者: 責(zé)怪 時(shí)間: 2025-3-28 05:02 作者: AVOID 時(shí)間: 2025-3-28 09:56
Learning Commutative Regular Languagesive samples, and then we study the possible improvement of inference from positive and negative samples. We propose a polynomial algorithm to infer commutative regular languages from positive and negative samples, and we show, from experimental results, that far from being a theoretical algorithm, i作者: Sedative 時(shí)間: 2025-3-28 12:04
Learning Left-to-Right and Right-to-Left Iterative Languagesiable in the limit from positive data. Essentially, these language classes are the ones obtained by merging final states in a prefix tree and initial states in a suffix tree of the observed sample, respectively. Strikingly, these classes are also transparently related to the zero-reversible language作者: 無力更進(jìn) 時(shí)間: 2025-3-28 15:40 作者: incontinence 時(shí)間: 2025-3-28 19:13
On Learning Regular Expressions and Patterns Via Membership and Correction Queriesuery, the oracle, in the case of negative answer, returns also a . – a positive datum (that has not been seen in the learning process yet) with the smallest edit distance from the queried string. Polynomial-time algorithms for learning a class of regular expressions from one such query and membershi作者: 主動(dòng) 時(shí)間: 2025-3-29 00:02
State-Merging DFA Induction Algorithms with Mandatory Merge ConstraintsIn particular, the negative information prevents merging incompatible states: merging those states would lead to produce an inconsistent DFA. Whenever available, domain knowledge can also be used to extend the set of incompatible states. We introduce here mandatory merge constraints, which form the 作者: CRUMB 時(shí)間: 2025-3-29 06:02 作者: Inertia 時(shí)間: 2025-3-29 10:41
Towards Feasible PAC-Learning of Probabilistic Deterministic Finite Automatated by Probabilistic Deterministic Finite Automata (PDFA). Our algorithm is an attempt to keep the rigorous guarantees of the original one but use sample sizes that are not as astronomical as predicted by the theory. We prove that indeed our algorithm PAC-learns in a stronger sense than the Clark-Th作者: SMART 時(shí)間: 2025-3-29 13:18 作者: Directed 時(shí)間: 2025-3-29 15:47 作者: 尖酸一點(diǎn) 時(shí)間: 2025-3-29 22:11
How to Split Recursive Automatarammars to learn subclasses of context-free languages. The algorithms considered implement .. This new perspective also helps to understand how it is possible to control the combinatorial explosion that specialization techniques have to face, thanks to a typing approach.作者: Stress 時(shí)間: 2025-3-30 02:33 作者: 摻假 時(shí)間: 2025-3-30 07:09
Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclusteringcquires rules of an unknown PCFG through iterative biclustering of bigrams in the training corpus. Our analysis shows that this procedure uses a greedy approach to adding rules such that each set of rules that is added to the grammar results in the largest increase in the posterior of the grammar gi作者: 熱心 時(shí)間: 2025-3-30 09:42
Polynomial Distinguishability of Timed Automataitly, i.e., using numbers. Because timed automata use numbers to represent time, they can be exponentially more compact than models that model time implicitly, i.e., using states..We show three results that are essential in order to exactly determine when timed automata are efficiently identifiable 作者: overreach 時(shí)間: 2025-3-30 13:13 作者: 俗艷 時(shí)間: 2025-3-30 16:49 作者: 小步舞 時(shí)間: 2025-3-30 22:10
https://doi.org/10.34157/978-3-648-15833-3orithm uses a representation which we call Binary Feature Grammars based on a set of features, capable of representing richly structured context free languages as well as some context sensitive languages. More precisely, we focus on a particular case of this representation where the features corresp作者: 諂媚于人 時(shí)間: 2025-3-31 03:49
,Wieviel Akzeptanz ertr?gt der Mensch?,ver, when to the question of converging to a target one adds computational constraints, the picture becomes even less clear: how much do queries or negative examples help? Can we find good algorithms that change their minds very little or that make very few errors? In order to approach these problem作者: ventilate 時(shí)間: 2025-3-31 07:18
,Technik — Deutungen ihrer Entwicklung,awn according to a distribution defined by a rational stochastic language, .EES outputs a linear representation of a rational series which converges to the target. .EES can then be used to identify in the limit with probability one rational stochastic tree languages. However, when .EES deals with fi作者: 類似思想 時(shí)間: 2025-3-31 09:19 作者: phlegm 時(shí)間: 2025-3-31 15:07 作者: 展覽 時(shí)間: 2025-3-31 18:22
Katja Kanzler,Brigitte Georgi-Findlayble tree languages of arbitrarily many dimensions, so-called multi-dimensional trees. Trees over multi-dimensional tree domains have been defined by Rogers [3,4]. However, since the algorithm by Drewes and H?gberg relies on classical finite state automata, these structures have to be represented in 作者: Trypsin 時(shí)間: 2025-3-31 23:16 作者: Abominate 時(shí)間: 2025-4-1 03:15
https://doi.org/10.1007/978-3-642-78272-5In particular, the negative information prevents merging incompatible states: merging those states would lead to produce an inconsistent DFA. Whenever available, domain knowledge can also be used to extend the set of incompatible states. We introduce here mandatory merge constraints, which form the 作者: aptitude 時(shí)間: 2025-4-1 08:46 作者: Bucket 時(shí)間: 2025-4-1 10:20 作者: GLOSS 時(shí)間: 2025-4-1 15:11
https://doi.org/10.1007/978-3-642-58802-0ased on a representation theorem induced by two operations over strings: duplication and reversal. The inference method produces an acceptor device which is an unconventional model of computation based on biomolecules (.). We prove that a subclass of context-sensitive languages can be inferred by us作者: 諄諄教誨 時(shí)間: 2025-4-1 20:13 作者: 流利圓滑 時(shí)間: 2025-4-1 22:41 作者: 無孔 時(shí)間: 2025-4-2 06:42
Umsetzungsbeispiele und Lessons Learned,odel [1], the forerunner of today’s active learning field. But the initial types of queries have some drawbacks: equivalence queries are both unrealistic and computationally costly; membership queries, on the other hand, are not informative enough, not being able to capture the feedback received by 作者: 打谷工具 時(shí)間: 2025-4-2 09:07
