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Viacjazykové LSTM×Long Short-Term Memory (LSTM)×
OdborHlboké učenieHlboké učenie
RodinaMachine learningMachine learning
Rok vzniku1997 (LSTM); multilingual NLP applications from ~20161997
TvorcaHochreiter, S. & Schmidhuber, J. (LSTM base); multilingual application by the NLP community from ~2016Hochreiter, S. & Schmidhuber, J.
TypRecurrent neural network (sequence model)Recurrent neural network with gated memory cells
Pôvodný zdrojHochreiter, S. & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735–1780. DOI ↗Hochreiter, S. & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8), 1735–1780. DOI ↗
Ďalšie názvyMultilingual LSTM, Cross-lingual LSTM, Multi-language LSTM, Multilingual Recurrent NetworkLSTM, LSTM network, LSTM-RNN, long short-term memory RNN
Príbuzné54
ZhrnutieA Multilingual LSTM is a Long Short-Term Memory recurrent network trained or fine-tuned to process sequences in multiple languages, typically by sharing a single model across language-specific or joint subword embeddings. It captures long-range dependencies in text and is applied to multilingual classification, named entity recognition, sentiment analysis, and sequence labeling.Long Short-Term Memory (LSTM) is a gated recurrent neural network architecture introduced by Hochreiter and Schmidhuber in 1997. It was designed to learn dependencies across long sequences by using dedicated memory cells and three learned gates — forget, input, and output — that control what information is retained, updated, or passed forward at each time step.
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ScholarGatePorovnať metódy: Multilingual LSTM · Long Short-Term Memory. Získané 2026-06-19 z https://scholargate.app/sk/compare