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樓主: APL
31#
發(fā)表于 2025-3-26 21:07:12 | 只看該作者
Dynamic grammatical representations in guided propagation networks, to complete internal representations in the course of processing allow noisy pattern parsing. Structured representations are obtained through extraction of syntactical substructures using different strategies. A comparison with classical grammar representation is presented.
32#
發(fā)表于 2025-3-27 04:28:49 | 只看該作者
A hybrid connectionist-symbolic approach to regular grammatical inference based on neural learning have been suggested to extract a finite state automaton (FSA) from the activation patterns of a trained net. However, the consistency with the examples of the extracted FSA is not guaranteed in these methods, and typically, some parameter of the clustering algorithm must be set arbitrarily (e.g. th
33#
發(fā)表于 2025-3-27 08:14:39 | 只看該作者
B. de Kruijff,P. R. Cullis,A. J. Verkleijthe number of examples required for learning is polynomial, the computational problem associated with learning is intractable..Learning homomorphisms is a simple special case of the general model. While a general method for learning homomorphisms is not known, it is shown that even if the target lan
34#
發(fā)表于 2025-3-27 10:17:32 | 只看該作者
https://doi.org/10.1007/978-1-4684-4850-4c theorems. This framework enables to state the regular inference problem as a search through a boolean lattice built from the positive sample. Several properties of the search space are studied and generalization criteria are discussed. In this framework, the concept of . is introduced, that is the
35#
發(fā)表于 2025-3-27 16:05:57 | 只看該作者
Membranfiltration im Molkereiwesen,e have developed a class-based bigram model determined entirely automatically from written text corpora. The classes are not defined, the words are not tagged, the solely assumption is the number of classes..We get a robust model which insures a more complete coverage of the succession probabilities
36#
發(fā)表于 2025-3-27 19:20:28 | 只看該作者
37#
發(fā)表于 2025-3-28 00:31:01 | 只看該作者
https://doi.org/10.1007/978-94-017-6123-9icted not only from the two immediately preceeding words, but potentially from any preceeding pair of adjacent words that lie within the same sentence. In this way, the trigram model can skip over less informative words to make its predictions. The underlying “grammar” is nothing more than a list of
38#
發(fā)表于 2025-3-28 02:46:40 | 只看該作者
Memorialization in Germany since 1945defined from a conceptually constrained task which was recently proposed within the field of Cognitive Science. Large corpora of English-to-Spanish and English-to-German translations have been generated, and exhaustive experiments have been carried out to test the ability of OSTIA to learn these tra
39#
發(fā)表于 2025-3-28 08:06:00 | 只看該作者
40#
發(fā)表于 2025-3-28 12:23:19 | 只看該作者
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