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楼主: Encomium
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Menschenrechte und europäische Außenpolitike of variables is a novel feature of CMM. It not only generalized the way subsequences can be matched, it also turns CMM from a pure sequence prediction algorithm into a computational model. I will show that CMM has sufficient expressiveness to represent any .. Thus it is not only capable of predict
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Selection criteria for word trigger pairs in language modeling,s approach produced better word trigger pairs than the conventional mutual information criterion. When used on the Wall Street Journal corpus, the trigger pairs selected reduced the perplexity of a trigram/cache language model from 138 to 128 for a 5-million word training set and from 92 to 87 for a
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Discrete sequence prediction with commented Markov models,e of variables is a novel feature of CMM. It not only generalized the way subsequences can be matched, it also turns CMM from a pure sequence prediction algorithm into a computational model. I will show that CMM has sufficient expressiveness to represent any .. Thus it is not only capable of predict
发表于 2025-4-2 07:49:18 | 显示全部楼层
Lexical categorization: Fitting template grammars by incremental MDL optimization,
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Grammatical Inference: Learning Syntax from Sentences
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