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21#
發(fā)表于 2025-3-25 04:00:05 | 只看該作者
Learning regular grammars to model musical style: Comparing different coding schemes,ed the need of a proper music coding scheme. Different coding schemes are presented and compared according to results in Composition and Style Recognition. Results from previous studies have been improved.
22#
發(fā)表于 2025-3-25 08:24:37 | 只看該作者
The Anatomy of Biological InterfacesIncorporating the suggestions made in De la Higuera, Vidal and Oncina [dOV96] for automata inference, the DD-OSTIA (Data Driven OSTIA) is presented here. The experiments show a great reduction of the size of the training set needed for obtaining good models.
23#
發(fā)表于 2025-3-25 14:47:57 | 只看該作者
Transmembrane Calcium Fluxes and Cell Deathations beyond the training set, in the language recognized by the extracted automaton, are due to the training regime: the network performs a “l(fā)oose” minimization of the . of the training set, the automaton that has a state for each prefix of the sentences in the set.
24#
發(fā)表于 2025-3-25 19:46:28 | 只看該作者
https://doi.org/10.1007/978-3-642-68077-9is now possible, although still very difficult, to build computational and formal models of how children learn language. This paper will review some recent developments in computational modeling of language acquisition and suggest how they might be extended to grammatical inference.
25#
發(fā)表于 2025-3-25 23:02:32 | 只看該作者
Angelo Azzi,Lanfranco Masotti,Arnaldo Vecliup as one of the two winners in that competition. The second winning algorithm, first proposed by Rodney Price, implements a new evidence-driven heuristic for state merging. Our own version of this heuristic is also described in this paper and compared to SAGE.
26#
發(fā)表于 2025-3-26 01:34:05 | 只看該作者
27#
發(fā)表于 2025-3-26 06:19:22 | 只看該作者
Membrane Structure and Propertiesessibility and distinguishability of the target STs has been evaluated. As a general result, a decrease of the sample density has been found as these parameters increase, suggesting that accessibility and distinguishability are parameters as important as the number of states to evaluate learnability of STs.
28#
發(fā)表于 2025-3-26 12:00:15 | 只看該作者
Peter S. Linsley,Manjusri Das,C. Fred Foxe in the limit if structural information is presented. Furthermore, we give a definition of a characteristic structural set for any target grammar. Finally we present the conclusions of the work and some guidelines for future works.
29#
發(fā)表于 2025-3-26 15:34:17 | 只看該作者
Meaning helps learning syntax,s an isomorphism applying to trees and allowing to automatically translate sentences into their semantic representation(s). Simple simulations of a learning algorithm are extensively developed and discussed.
30#
發(fā)表于 2025-3-26 19:56:54 | 只看該作者
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