Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Rrjeti Neurale Rekurent Multilingual× | Rrjeti Nervor Rekurent× | |
|---|---|---|
| Fusha | Mësimi i thellë | Mësimi i thellë |
| Familja | Machine learning | Machine learning |
| Viti i origjinës≠ | 1990–2010s | 1986–1990 |
| Krijuesi≠ | Elman, J. L. (RNN); multilingual extension by NLP community | Rumelhart, D. E.; Elman, J. L. |
| Lloji≠ | Sequential model (cross-lingual) | Sequential neural network |
| Burimi themelues | Elman, J. L. (1990). Finding structure in time. Cognitive Science, 14(2), 179–211. DOI ↗ | Elman, J. L. (1990). Finding structure in time. Cognitive Science, 14(2), 179–211. DOI ↗ |
| Emërtime të tjera | Multilingual RNN, Cross-lingual RNN, Multi-language RNN, MRNN | RNN, Elman network, Jordan network, simple recurrent network |
| Të lidhura≠ | 5 | 3 |
| Përmbledhja≠ | A Multilingual Recurrent Neural Network (Multilingual RNN) applies the standard RNN architecture — which processes sequences step by step while maintaining a hidden state — to data spanning two or more languages. By training on multilingual corpora or sharing parameters across languages, the model learns cross-lingual sequence representations useful for translation, tagging, classification, and language modeling tasks. | A Recurrent Neural Network (RNN) is a class of neural network designed to process sequential data by maintaining a hidden state that carries information across time steps. Introduced in its modern form by Rumelhart et al. (1986) and further shaped by Elman (1990), RNNs became the dominant architecture for sequence modelling in NLP, speech, and time-series analysis before the rise of attention-based models. |
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